18+ EMR Jobs in India

Role Proficiency:

This role requires proficiency in developing data pipelines including coding and testing for ingesting wrangling transforming and joining data from various sources. The ideal candidate should be adept in ETL tools like Informatica Glue Databricks and DataProc with strong coding skills in Python PySpark and SQL. This position demands independence and proficiency across various data domains. Expertise in data warehousing solutions such as Snowflake BigQuery Lakehouse and Delta Lake is essential including the ability to calculate processing costs and address performance issues. A solid understanding of DevOps and infrastructure needs is also required.

Skill Examples:

1. Proficiency in SQL Python or other programming languages used for data manipulation.
2. Experience with ETL tools such as Apache Airflow Talend Informatica AWS Glue Dataproc and Azure ADF.
3. Hands-on experience with cloud platforms like AWS Azure or Google Cloud particularly with data-related services (e.g. AWS Glue BigQuery).
4. Conduct tests on data pipelines and evaluate results against data quality and performance specifications.
5. Experience in performance tuning.
6. Experience in data warehouse design and cost improvements.
7. Apply and optimize data models for efficient storage retrieval and processing of large datasets.
8. Communicate and explain design/development aspects to customers.
9. Estimate time and resource requirements for developing/debugging features/components.
10. Participate in RFP responses and solutioning.
11. Mentor team members and guide them in relevant upskilling and certification.

Knowledge Examples:

1. Knowledge of various ETL services used by cloud providers including Apache PySpark AWS Glue GCP DataProc/Dataflow Azure ADF and ADLF.
2. Proficient in SQL for analytics and windowing functions.
3. Understanding of data schemas and models.
4. Familiarity with domain-related data.
5. Knowledge of data warehouse optimization techniques.
6. Understanding of data security concepts.
7. Awareness of patterns frameworks and automation practices.

Additional Comments:

# of Resources: 22 Role(s): Technical Role Location(s): India Planned Start Date: 1/1/2026 Planned End Date: 6/30/2026

Project Overview:

Role Scope / Deliverables: We are seeking highly skilled Data Engineer with strong experience in Databricks, PySpark, Python, SQL, and AWS to join our data engineering team on or before 1st week of Dec, 2025.

The candidate will be responsible for designing, developing, and optimizing large-scale data pipelines and analytics solutions that drive business insights and operational efficiency.

Design, build, and maintain scalable data pipelines using Databricks and PySpark.

Develop and optimize complex SQL queries for data extraction, transformation, and analysis.

Implement data integration solutions across multiple AWS services (S3, Glue, Lambda, Redshift, EMR, etc.).

Collaborate with analytics, data science, and business teams to deliver clean, reliable, and timely datasets.

Ensure data quality, performance, and reliability across data workflows.

Participate in code reviews, data architecture discussions, and performance optimization initiatives.

Support migration and modernization efforts for legacy data systems to modern cloud-based solutions.

Key Skills:

Hands-on experience with Databricks, PySpark & Python for building ETL/ELT pipelines.

Proficiency in SQL (performance tuning, complex joins, CTEs, window functions).

Strong understanding of AWS services (S3, Glue, Lambda, Redshift, CloudWatch, etc.).

Experience with data modeling, schema design, and performance optimization.

Familiarity with CI/CD pipelines, version control (Git), and workflow orchestration (Airflow preferred).

Excellent problem-solving, communication, and collaboration skills.

Skills: Databricks, Pyspark & Python, Sql, Aws Services

Must-Haves

Python/PySpark (5+ years), SQL (5+ years), Databricks (3+ years), AWS Services (3+ years), ETL tools (Informatica, Glue, DataProc) (3+ years)

Hands-on experience with Databricks, PySpark & Python for ETL/ELT pipelines.

Proficiency in SQL (performance tuning, complex joins, CTEs, window functions).

Strong understanding of AWS services (S3, Glue, Lambda, Redshift, CloudWatch, etc.).

Experience with data modeling, schema design, and performance optimization.

Familiarity with CI/CD pipelines, Git, and workflow orchestration (Airflow preferred).

******

Notice period - Immediate to 15 days

Location: Bangalore

ROLE & RESPONSIBILITIES:

We are hiring a Senior DevSecOps / Security Engineer with 8+ years of experience securing AWS cloud, on-prem infrastructure, DevOps platforms, MLOps environments, CI/CD pipelines, container orchestration, and data/ML platforms. This role is responsible for creating and maintaining a unified security posture across all systems used by DevOps and MLOps teams — including AWS, Kubernetes, EMR, MWAA, Spark, Docker, GitOps, observability tools, and network infrastructure.

KEY RESPONSIBILITIES:

1.     Cloud Security (AWS)-

• Secure all AWS resources consumed by DevOps/MLOps/Data Science: EC2, EKS, ECS, EMR, MWAA, S3, RDS, Redshift, Lambda, CloudFront, Glue, Athena, Kinesis, Transit Gateway, VPC Peering.
• Implement IAM least privilege, SCPs, KMS, Secrets Manager, SSO & identity governance.
• Configure AWS-native security: WAF, Shield, GuardDuty, Inspector, Macie, CloudTrail, Config, Security Hub.
• Harden VPC architecture, subnets, routing, SG/NACLs, multi-account environments.
• Ensure encryption of data at rest/in transit across all cloud services.

2.     DevOps Security (IaC, CI/CD, Kubernetes, Linux)-

Infrastructure as Code & Automation Security:

• Secure Terraform, CloudFormation, Ansible with policy-as-code (OPA, Checkov, tfsec).
• Enforce misconfiguration scanning and automated remediation.

CI/CD Security:

• Secure Jenkins, GitHub, GitLab pipelines with SAST, DAST, SCA, secrets scanning, image scanning.
• Implement secure build, artifact signing, and deployment workflows.

Containers & Kubernetes:

• Harden Docker images, private registries, runtime policies.
• Enforce EKS security: RBAC, IRSA, PSP/PSS, network policies, runtime monitoring.
• Apply CIS Benchmarks for Kubernetes and Linux.

Monitoring & Reliability:

• Secure observability stack: Grafana, CloudWatch, logging, alerting, anomaly detection.
• Ensure audit logging across cloud/platform layers.

3.     MLOps Security (Airflow, EMR, Spark, Data Platforms, ML Pipelines)-

Pipeline & Workflow Security:

• Secure Airflow/MWAA connections, secrets, DAGs, execution environments.
• Harden EMR, Spark jobs, Glue jobs, IAM roles, S3 buckets, encryption, and access policies.

ML Platform Security:

• Secure Jupyter/JupyterHub environments, containerized ML workspaces, and experiment tracking systems.
• Control model access, artifact protection, model registry security, and ML metadata integrity.

Data Security:

• Secure ETL/ML data flows across S3, Redshift, RDS, Glue, Kinesis.
• Enforce data versioning security, lineage tracking, PII protection, and access governance.

ML Observability:

• Implement drift detection (data drift/model drift), feature monitoring, audit logging.
• Integrate ML monitoring with Grafana/Prometheus/CloudWatch.

4.     Network & Endpoint Security-

• Manage firewall policies, VPN, IDS/IPS, endpoint protection, secure LAN/WAN, Zero Trust principles.
• Conduct vulnerability assessments, penetration test coordination, and network segmentation.
• Secure remote workforce connectivity and internal office networks.

5.     Threat Detection, Incident Response & Compliance-

• Centralize log management (CloudWatch, OpenSearch/ELK, SIEM).
• Build security alerts, automated threat detection, and incident workflows.
• Lead incident containment, forensics, RCA, and remediation.
• Ensure compliance with ISO 27001, SOC 2, GDPR, HIPAA (as applicable).
• Maintain security policies, procedures, RRPs (Runbooks), and audits.

IDEAL CANDIDATE:

• 8+ years in DevSecOps, Cloud Security, Platform Security, or equivalent.
• Proven ability securing AWS cloud ecosystems (IAM, EKS, EMR, MWAA, VPC, WAF, GuardDuty, KMS, Inspector, Macie).
• Strong hands-on experience with Docker, Kubernetes (EKS), CI/CD tools, and Infrastructure-as-Code.
• Experience securing ML platforms, data pipelines, and MLOps systems (Airflow/MWAA, Spark/EMR).
• Strong Linux security (CIS hardening, auditing, intrusion detection).
• Proficiency in Python, Bash, and automation/scripting.
• Excellent knowledge of SIEM, observability, threat detection, monitoring systems.
• Understanding of microservices, API security, serverless security.
• Strong understanding of vulnerability management, penetration testing practices, and remediation plans.

EDUCATION:

• Master’s degree in Cybersecurity, Computer Science, Information Technology, or related field.
• Relevant certifications (AWS Security Specialty, CISSP, CEH, CKA/CKS) are a plus.

PERKS, BENEFITS AND WORK CULTURE:

• Competitive Salary Package
• Generous Leave Policy
• Flexible Working Hours
• Performance-Based Bonuses
• Health Care Benefits

Review Criteria

• Strong MLOps profile
• 8+ years of DevOps experience and 4+ years in MLOps / ML pipeline automation and production deployments
• 4+ years hands-on experience in Apache Airflow / MWAA managing workflow orchestration in production
• 4+ years hands-on experience in Apache Spark (EMR / Glue / managed or self-hosted) for distributed computation
• Must have strong hands-on experience across key AWS services including EKS/ECS/Fargate, Lambda, Kinesis, Athena/Redshift, S3, and CloudWatch
• Must have hands-on Python for pipeline & automation development
• 4+ years of experience in AWS cloud, with recent companies
• (Company) - Product companies preferred; Exception for service company candidates with strong MLOps + AWS depth

Preferred

• Hands-on in Docker deployments for ML workflows on EKS / ECS
• Experience with ML observability (data drift / model drift / performance monitoring / alerting) using CloudWatch / Grafana / Prometheus / OpenSearch.
• Experience with CI / CD / CT using GitHub Actions / Jenkins.
• Experience with JupyterHub/Notebooks, Linux, scripting, and metadata tracking for ML lifecycle.
• Understanding of ML frameworks (TensorFlow / PyTorch) for deployment scenarios.

Job Specific Criteria

• CV Attachment is mandatory
• Please provide CTC Breakup (Fixed + Variable)?
• Are you okay for F2F round?
• Have candidate filled the google form?

Role & Responsibilities

We are looking for a Senior MLOps Engineer with 8+ years of experience building and managing production-grade ML platforms and pipelines. The ideal candidate will have strong expertise across AWS, Airflow/MWAA, Apache Spark, Kubernetes (EKS), and automation of ML lifecycle workflows. You will work closely with data science, data engineering, and platform teams to operationalize and scale ML models in production.

Key Responsibilities:

• Design and manage cloud-native ML platforms supporting training, inference, and model lifecycle automation.
• Build ML/ETL pipelines using Apache Airflow / AWS MWAA and distributed data workflows using Apache Spark (EMR/Glue).
• Containerize and deploy ML workloads using Docker, EKS, ECS/Fargate, and Lambda.
• Develop CI/CT/CD pipelines integrating model validation, automated training, testing, and deployment.
• Implement ML observability: model drift, data drift, performance monitoring, and alerting using CloudWatch, Grafana, Prometheus.
• Ensure data governance, versioning, metadata tracking, reproducibility, and secure data pipelines.
• Collaborate with data scientists to productionize notebooks, experiments, and model deployments.

Ideal Candidate

• 8+ years in MLOps/DevOps with strong ML pipeline experience.
• Strong hands-on experience with AWS:
• Compute/Orchestration: EKS, ECS, EC2, Lambda
• Data: EMR, Glue, S3, Redshift, RDS, Athena, Kinesis
• Workflow: MWAA/Airflow, Step Functions
• Monitoring: CloudWatch, OpenSearch, Grafana
• Strong Python skills and familiarity with ML frameworks (TensorFlow/PyTorch/Scikit-learn).
• Expertise with Docker, Kubernetes, Git, CI/CD tools (GitHub Actions/Jenkins).
• Strong Linux, scripting, and troubleshooting skills.
• Experience enabling reproducible ML environments using Jupyter Hub and containerized development workflows.

Education:

• Master’s degree in computer science, Machine Learning, Data Engineering, or related field.

We are seeking an experienced Technical Delivery lead with expertise in healthcare technology to lead and manage EMR, EHR, FHIR, and interoperability projects. The ideal candidate will have a strong background in Fullstack /MERN stack development, and healthcare data standards. This role requires leadership in solution delivery, stakeholder management, team collaboration, and agile project Responsibilities : Project Delivery & Execution

 Oversee end-to-end delivery of EMR, EHR, FHIR, and healthcare interoperability solutions.

 Ensure adherence to healthcare compliance standards (HIPAA, HL7, FHIR, USCDI, etc.).

 Drive agile methodologies (Scrum/Kanban) for project Leadership :

 Lead teams in Fullstack / MERN development.

 Provide guidance on FHIR, HL7, EL7, and interoperability standards.

 Project Planning and Execution: Create and manage detailed project plans, including scope, objectives, timelines, resources, and budgets, to ensure successful delivery of healthcare projects.

 Stakeholder Collaboration: Engage with healthcare professionals, administrators, IT teams, and external vendors to define project requirements, ensure alignment, and maintain stakeholder satisfaction.

 Team Leadership: Lead cross-functional teams, delegating tasks, resolving conflicts, and fostering collaboration to meet project milestones.

 Architect and implement scalable, secure, and compliant healthcare & Client Management :

 Collaborate with healthcare providers, payers, and regulatory bodies.

 Translate business needs into technical requirements and solutions.

 Ensure smooth communication between technical teams and business Management & Mentoring :

 Manage a cross-functional team of developers, architects, and QA engineers.

 Provide mentorship and training on EMR/EHR systems, APIs, and cloud & Continuous Improvement :

 Keep up with the latest healthcare IT trends, FHIR updates, and interoperability advancements.

 Drive best practices in CI/CD, microservices, and API Skills & Qualifications :

 10+ years of experience in software development and Technical project management.

 Deliver projects deliverables from inception to delivery on time and meet all project requirements

 Work with stakeholders to set timelines, communicate program statuses, set recurring meetings, and identify/address potential setbacks

 Able to use JIRA to plan and track project development and timelines

 Work with department heads and other team leaders to ensure project objectives are met

 Work closely with our Product and Engineering teams to communicate customer feedback and drive product improvements

 Strong expertise in EMR, EHR, FHIR, HL7, interoperability standards.

 Hands-on experience in MERN Stack software development

 Knowledge of FHIR-based data exchange, SMART on FHIR, and USCDI.

 Experience with authentication protocols (OAuth2, JWT, SAML, OpenID Connect).

 Proficiency in agile project management (Scrum, SAFe, Kanban).

 Strong leadership, problem-solving, and communication Qualifications :

 Experience with FHIR servers like Azure API for FHIR, HAPI FHIR.

 Exposure to AI/ML in healthcare, predictive analytics, and data interoperability.

 PMP, SAFe, or Agile certification is a plus.

Position Overview:

We are seeking a highly motivated and skilled Real-World Evidence (RWE) Analyst to join growing team. The successful candidate will be instrumental in generating crucial insights from real-world healthcare data to inform decision-making, improve patient outcomes, and advance medical understanding. This role offers an exciting opportunity to work with diverse healthcare datasets and contribute to impactful research that drives real-world change.

Key Responsibilities:

For Both RWE Analyst (Junior) & Senior RWE Analyst:

• Data Expertise: Work extensively with real-world healthcare data, including Electronic Medical Records (EMR), claims data, and/or patient registries. (Experience with clinical trial data does not fulfill this requirement.)
• Methodology: Apply appropriate statistical and epidemiological methodologies to analyze complex healthcare datasets.
• Communication: Clearly communicate findings through presentations, reports, and data visualizations to both technical and non-technical audiences.
• Collaboration: Collaborate effectively with cross-functional teams, including clinicians, epidemiologists, statisticians, and data scientists.
• Quality Assurance: Ensure the accuracy, reliability, and validity of all analyses and reports.
• Ethical Conduct: Adhere to all relevant data privacy regulations and ethical guidelines in real-world data research.

Specific Responsibilities for RWE Analyst (Junior):

• Perform statistical analysis on real-world healthcare datasets under guidance.
• Contribute to the development of analysis plans, often by implementing predefined methodologies or refining existing approaches.
• Prepare and clean data for analysis, identifying and addressing data quality issues.
• Assist in the interpretation of study results and the drafting of reports or presentations.
• Support the preparation of journal publication materials based on RWE studies.

Specific Responsibilities for Senior RWE Analyst:

• Analysis Design & Leadership: Independently design and develop comprehensive analysis plans from inception for RWE studies, identifying appropriate methodologies, data sources, and analytical approaches. This role requires a "thinker" who can conceptualize and drive the analytical strategy, not just execute pre-defined requests.
• Project Management: Lead and manage RWE projects from conception to completion, ensuring timely delivery and high-quality outputs.
• Mentorship: Mentor and guide junior RWE analysts, fostering their development in real-world data analysis and research.
• Methodological Innovation: Proactively identify and evaluate new methodologies and technologies to enhance RWE capabilities.
• Strategic Input: Provide strategic input on study design, data acquisition, and evidence generation strategies.

Qualifications:

For Both RWE Analyst (Junior) & Senior RWE Analyst:

• Bachelor's or Master's degree in Epidemiology, Biostatistics, Public Health, Health Economics, Data Science, or a related quantitative field. (PhD preferred for Senior RWE Analyst).
• Demonstrable hands-on experience working with real-world healthcare data, specifically EMR, claims, and/or registry data. Clinical trial data experience will not be considered as meeting this requirement.
• Proficiency in at least one statistical programming language (e.g., R, Python, SAS, SQL).
• Strong understanding of epidemiological study designs and statistical methods relevant to RWE.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong written and verbal communication skills.

Specific Qualifications for RWE Analyst (Junior):

• 4+ years of experience in real-world data analysis in a healthcare or pharmaceutical setting.
• Involvement with journal publications is highly desirable. (e.g., co-authorship, contribution to manuscript preparation).

Specific Qualifications for Senior RWE Analyst:

• 5+ years of progressive experience in real-world data analysis, with a significant portion dedicated to independent study design and leadership.
• A strong track record of journal publications is essential. (e.g., lead author, significant contribution to multiple peer-reviewed publications).
• Proven ability to translate complex analytical findings into actionable insights for diverse stakeholders.
• Experience with advanced analytical techniques (e.g., machine learning, causal inference) is a plus.

Preferred Skills (for both roles, but more emphasized for Senior):

• Experience with large healthcare databases (e.g., IQVIA, Optum, IBM MarketScan, SEER, NDHM).
• Knowledge of common data models (e.g., OMOP CDM).
• Familiarity with regulatory guidelines and best practices for RWE generation.

Hi,

This is Prashant, a Senior Recruiter from Triunity Software Inc. a leading staffing organization.

Title: Staff Software Engineer with Cloud & Healthcare Experience (Need Local Candidates)

Job Location: Hyderabad, India, Hybrid with 3-days a week at our Offshore location

Job Summary:

Responsible for full stack software definition, development and maintenance for cloud-based software applications used in healthcare. Specifically, responsible for all external interfaces with the cloud applications. Work closely with the Cloud Engineering team, Project leaders to define requirements, develop code and conduct unit and system-level tests for the software you develop.

Job Responsibilities (but not limited to):

·    Work closely with Cloud Engineering team members in architecting and designing cloud- based solutions.

·    Ultrasound DICOM and Electronic Medical Record (EMR) interfaces.

·    OAuth and Single Sign-on (SSO) interfaces with cloud applications.

·    Workflow engine that automates and manages workflows in the applications.

·    Assist in the architecture, design, and deployment of the full stack product.

·    Build software that meets HIPAA and Cybersecurity requirements for medical products.

·    Be part of a small, cross-functional product team working alongside product managers, design engineers, clinical engineers and software engineers.

·    Meet all Quality Management System (QMS) requirements for design, development, testing and product release.

Minimum Education/Experience:

·    Bachelor’s degree in computer science or Equivalent

·    10+ years of software development experience with Python, Django and TypeScript/JavaScript.

·    Experience with Terraform, CI/CD and AWS.

·    Familiarity with medical imaging and interface protocols used in healthcare including DICOM, HL7, FIHR, LDAP and Single Sign-on (SSO) if preferable.

Thanks & Regards

Prashant Rathore |Sr.IT Recruiter| Triunity Software Inc.

Greetings , Wissen Technology is Hiring for the position of Data Engineer

Please find the Job Description for your Reference:

JD

• Design, develop, and maintain data pipelines on AWS EMR (Elastic MapReduce) to support data processing and analytics.
• Implement data ingestion processes from various sources including APIs, databases, and flat files.
• Optimize and tune big data workflows for performance and scalability.
• Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions.
• Manage and monitor EMR clusters, ensuring high availability and reliability.
• Develop ETL (Extract, Transform, Load) processes to cleanse, transform, and store data in data lakes and data warehouses.
• Implement data security best practices to ensure data is protected and compliant with relevant regulations.
• Create and maintain technical documentation related to data pipelines, workflows, and infrastructure.
• Troubleshoot and resolve issues related to data processing and EMR cluster performance.

Qualifications:

• Bachelor’s degree in Computer Science, Information Technology, or a related field.
• 5+ years of experience in data engineering, with a focus on big data technologies.
• Strong experience with AWS services, particularly EMR, S3, Redshift, Lambda, and Glue.
• Proficiency in programming languages such as Python, Java, or Scala.
• Experience with big data frameworks and tools such as Hadoop, Spark, Hive, and Pig.
• Solid understanding of data modeling, ETL processes, and data warehousing concepts.
• Experience with SQL and NoSQL databases.
• Familiarity with CI/CD pipelines and version control systems (e.g., Git).
• Strong problem-solving skills and the ability to work independently and collaboratively in a team environment

Responsibilities:

• Design, implement, and maintain scalable and reliable database solutions on the AWS platform.
• Architect, deploy, and optimize DynamoDB databases for performance, scalability, and cost-efficiency.
• Configure and manage AWS OpenSearch (formerly Amazon Elasticsearch Service) clusters for real-time search and analytics capabilities.
• Design and implement data processing and analytics solutions using AWS EMR (Elastic MapReduce) for large-scale data processing tasks.
• Collaborate with cross-functional teams to gather requirements, design database solutions, and implement best practices.
• Perform performance tuning, monitoring, and troubleshooting of database systems to ensure high availability and performance.
• Develop and maintain documentation, including architecture diagrams, configurations, and operational procedures.
• Stay current with the latest AWS services, database technologies, and industry trends to provide recommendations for continuous improvement.
• Participate in the evaluation and selection of new technologies, tools, and frameworks to enhance database capabilities.
• Provide guidance and mentorship to junior team members, fostering knowledge sharing and skill development.

Requirements:

• Bachelor’s degree in computer science, Information Technology, or related field.
• Proven experience as an AWS Architect or similar role, with a focus on database technologies.
• Hands-on experience designing, implementing, and optimizing DynamoDB databases in production environments.
• In-depth knowledge of AWS OpenSearch (Elasticsearch) and experience configuring and managing clusters for search and analytics use cases.
• Proficiency in working with AWS EMR (Elastic MapReduce) for big data processing and analytics.
• Strong understanding of database concepts, data modelling, indexing, and query optimization.
• Experience with AWS services such as S3, EC2, RDS, Redshift, Lambda, and CloudFormation.
• Excellent problem-solving skills and the ability to troubleshoot complex database issues.
• Solid understanding of cloud security best practices and experience implementing security controls in AWS environments.
• Strong communication and collaboration skills with the ability to work effectively in a team environment.
• AWS certifications such as AWS Certified Solutions Architect, AWS Certified Database - Specialty, or equivalent certifications are a plus.

About Kloud9:

Kloud9 exists with the sole purpose of providing cloud expertise to the retail industry. Our team of cloud architects, engineers and developers help retailers launch a successful cloud initiative so you can quickly realise the benefits of cloud technology. Our standardised, proven cloud adoption methodologies reduce the cloud adoption time and effort so you can directly benefit from lower migration costs.

Kloud9 was founded with the vision of bridging the gap between E-commerce and cloud. The E-commerce of any industry is limiting and poses a huge challenge in terms of the finances spent on physical data structures.

At Kloud9, we know migrating to the cloud is the single most significant technology shift your company faces today. We are your trusted advisors in transformation and are determined to build a deep partnership along the way. Our cloud and retail experts will ease your transition to the cloud.

Our sole focus is to provide cloud expertise to retail industry giving our clients the empowerment that will take their business to the next level. Our team of proficient architects, engineers and developers have been designing, building and implementing solutions for retailers for an average of more than 20 years.

We are a cloud vendor that is both platform and technology independent. Our vendor independence not just provides us with a unique perspective into the cloud market but also ensures that we deliver the cloud solutions available that best meet our clients' requirements.

What we are looking for:

● 3+ years’ experience developing Data & Analytic solutions

● Experience building data lake solutions leveraging one or more of the following AWS, EMR, S3, Hive& Spark

● Experience with relational SQL

● Experience with scripting languages such as Shell, Python

● Experience with source control tools such as GitHub and related dev process

● Experience with workflow scheduling tools such as Airflow

● In-depth knowledge of scalable cloud

● Has a passion for data solutions

● Strong understanding of data structures and algorithms

● Strong understanding of solution and technical design

● Has a strong problem-solving and analytical mindset

● Experience working with Agile Teams.

● Able to influence and communicate effectively, both verbally and written, with team members and business stakeholders

● Able to quickly pick up new programming languages, technologies, and frameworks

● Bachelor’s Degree in computer science

Why Explore a Career at Kloud9:

With job opportunities in prime locations of US, London, Poland and Bengaluru, we help build your career paths in cutting edge technologies of AI, Machine Learning and Data Science. Be part of an inclusive and diverse workforce that's changing the face of retail technology with their creativity and innovative solutions. Our vested interest in our employees translates to deliver the best products and solutions to our customers.

Company Profile:

Easebuzz is a payment solutions (fintech organisation) company which enables online merchants to accept, process and disburse payments through developer friendly APIs. We are focusing on building plug n play products including the payment infrastructure to solve complete business problems. Definitely a wonderful place where all the actions related to payments, lending, subscription, eKYC is happening at the same time.

We have been consistently profitable and are constantly developing new innovative products, as a result, we are able to grow 4x over the past year alone. We are well capitalised and have recently closed a fundraise of $4M in March, 2021 from prominent VC firms and angel investors. The company is based out of Pune and has a total strength of 180 employees. Easebuzz’s corporate culture is tied into the vision of building a workplace which breeds open communication and minimal bureaucracy. An equal opportunity employer, we welcome and encourage diversity in the workplace. One thing you can be sure of is that you will be surrounded by colleagues who are committed to helping each other grow.

Easebuzz Pvt. Ltd. has its presence in Pune, Bangalore, Gurugram.

Salary: As per company standards.

Designation: Data Engineering

Location: Pune

Experience with ETL, Data Modeling, and Data Architecture

Design, build and operationalize large scale enterprise data solutions and applications using one or more of AWS data and analytics services in combination with 3rd parties
- Spark, EMR, DynamoDB, RedShift, Kinesis, Lambda, Glue.

Experience with AWS cloud data lake for development of real-time or near real-time use cases

Experience with messaging systems such as Kafka/Kinesis for real time data ingestion and processing

Build data pipeline frameworks to automate high-volume and real-time data delivery

Create prototypes and proof-of-concepts for iterative development.

Experience with NoSQL databases, such as DynamoDB, MongoDB etc

Create and maintain optimal data pipeline architecture,

Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.

Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies.

Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.

Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.

Keep our data separated and secure across national boundaries through multiple data centers and AWS regions.

Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.

Evangelize a very high standard of quality, reliability and performance for data models and algorithms that can be streamlined into the engineering and sciences workflow

Build and enhance data pipeline architecture by designing and implementing data ingestion solutions.

Employment Type

Full-time

We are looking for an outstanding ML Architect (Deployments) with expertise in deploying Machine Learning solutions/models into production and scaling them to serve millions of customers. A candidate with an adaptable and productive working style which fits in a fast-moving environment.

Skills:

- 5+ years deploying Machine Learning pipelines in large enterprise production systems.

- Experience developing end to end ML solutions from business hypothesis to deployment / understanding the entirety of the ML development life cycle.
- Expert in modern software development practices; solid experience using source control management (CI/CD).
- Proficient in designing relevant architecture / microservices to fulfil application integration, model monitoring, training / re-training, model management, model deployment, model experimentation/development, alert mechanisms.
- Experience with public cloud platforms (Azure, AWS, GCP).
- Serverless services like lambda, azure functions, and/or cloud functions.
- Orchestration services like data factory, data pipeline, and/or data flow.
- Data science workbench/managed services like azure machine learning, sagemaker, and/or AI platform.
- Data warehouse services like snowflake, redshift, bigquery, azure sql dw, AWS Redshift.
- Distributed computing services like Pyspark, EMR, Databricks.
- Data storage services like cloud storage, S3, blob, S3 Glacier.
- Data visualization tools like Power BI, Tableau, Quicksight, and/or Qlik.
- Proven experience serving up predictive algorithms and analytics through batch and real-time APIs.
- Solid working experience with software engineers, data scientists, product owners, business analysts, project managers, and business stakeholders to design the holistic solution.
- Strong technical acumen around automated testing.
- Extensive background in statistical analysis and modeling (distributions, hypothesis testing, probability theory, etc.)
- Strong hands-on experience with statistical packages and ML libraries (e.g., Python scikit learn, Spark MLlib, etc.)
- Experience in effective data exploration and visualization (e.g., Excel, Power BI, Tableau, Qlik, etc.)
- Experience in developing and debugging in one or more of the languages Java, Python.
- Ability to work in cross functional teams.
- Apply Machine Learning techniques in production including, but not limited to, neuralnets, regression, decision trees, random forests, ensembles, SVM, Bayesian models, K-Means, etc.

Roles and Responsibilities:

Deploying ML models into production, and scaling them to serve millions of customers.

Technical solutioning skills with deep understanding of technical API integrations, AI / Data Science, BigData and public cloud architectures / deployments in a SaaS environment.

Strong stakeholder relationship management skills - able to influence and manage the expectations of senior executives.
Strong networking skills with the ability to build and maintain strong relationships with both business, operations and technology teams internally and externally.

Provide software design and programming support to projects.

 Qualifications & Experience:

Engineering and post graduate candidates, preferably in Computer Science, from premier institutions with proven work experience as a Machine Learning Architect (Deployments) or a similar role for 5-7 years.