Pyspark Developer

RESPONSIBILITIES:

 Requirement understanding and elicitation, analyze, data/workflows, contribute to product

project and Proof of concept (POC)

 Contribute to prepare design documents and effort estimations.

 Develop AI/ML Models using best in-class ML models.

 Building, testing, and deploying AI/ML solutions.

 Work with Business Analysts and Product Managers to assist with defining functional user

stories.

 Ensure deliverables across teams are of high quality and clearly documented. 

 Recommend best ML practices/Industry standards for any ML use case.

 Proactively take up R and D and recommend solution options for any ML use case.

REQUIREMENTS:

Required Skills

 Overall experience of 4 to 7 Years working on AI/ML framework development

 Good programming knowledge in Python is must.

 Good Knowledge of R and SAS is desired.

 Good hands on and working knowledge SQL, Data Model, CRISP-DM.

 Proficiency with Uni/multivariate statistics, algorithm design, and predictive AI/ML modelling.

 Strong knowledge of machine learning algorithms, linear regression, logistic regression, KNN,

Random Forest, Support Vector Machines and Natural Language Processing.

 Experience with NLP and deep neural networks using synthetic and artificial data.

 Involved in different phases of SDLC and have good working exposure on different SLDC’s like

Agile Methodologies.

Job Description: Data Engineer

Experience: Over 4 years

Responsibilities:

-       Design, develop, and maintain scalable data pipelines for efficient data extraction, transformation, and loading (ETL) processes.

-       Architect and implement data storage solutions, including data warehouses, data lakes, and data marts, aligned with business needs.

-       Implement robust data quality checks and data cleansing techniques to ensure data accuracy and consistency.

-       Optimize data pipelines for performance, scalability, and cost-effectiveness.

-       Collaborate with data analysts and data scientists to understand data requirements and translate them into technical solutions.

-       Develop and maintain data security measures to ensure data privacy and regulatory compliance.

-       Automate data processing tasks using scripting languages (Python, Bash) and big data frameworks (Spark, Hadoop).

-       Monitor data pipelines and infrastructure for performance and troubleshoot any issues.

-       Stay up to date with the latest trends and technologies in data engineering, including cloud platforms (AWS, Azure, GCP).

-        Document data pipelines, processes, and data models for maintainability and knowledge sharing.

-       Contribute to the overall data governance strategy and best practices.

Qualifications:

-       Strong understanding of data architectures, data modelling principles, and ETL processes.

-       Proficiency in SQL (e.g., MySQL, PostgreSQL) and experience with big data querying languages (e.g., Hive, Spark SQL).

-       Experience with scripting languages (Python, Bash) for data manipulation and automation.

-       Experience with distributed data processing frameworks (Spark, Hadoop) (preferred).

-       Familiarity with cloud platforms (AWS, Azure, GCP) for data storage and processing (a plus).

-       Experience with data quality tools and techniques.

-       Excellent problem-solving, analytical, and critical thinking skills.

-       Strong communication, collaboration, and teamwork abilities.

Sr. Data Engineer (Data Warehouse-Snowflake)

Experience: 5+yrs

Location: Pune (Hybrid)

As a Senior Data engineer with Snowflake expertise you are a subject matter expert who is curious and an innovative thinker to mentor young professionals. You are a key person to convert Vision and Data Strategy for Data solutions and deliver them. With your knowledge you will help create data-driven thinking within the organization, not just within Data teams, but also in the wider stakeholder community.

Skills Preferred

• Advanced written, verbal, and analytic skills, and demonstrated ability to influence and facilitate sustained change. Ability to convey information clearly and concisely to all levels of staff and management about programs, services, best practices, strategies, and organizational mission and values.
• Proven ability to focus on priorities, strategies, and vision.
• Very Good understanding in Data Foundation initiatives, like Data Modelling, Data Quality Management, Data Governance, Data Maturity Assessments and Data Strategy in support of the key business stakeholders.
• Actively deliver the roll-out and embedding of Data Foundation initiatives in support of the key business programs advising on the technology and using leading market standard tools.
• Coordinate the change management process, incident management and problem management process.
• Ensure traceability of requirements from Data through testing and scope changes, to training and transition.
• Drive implementation efficiency and effectiveness across the pilots and future projects to minimize cost, increase speed of implementation and maximize value delivery

Knowledge Preferred

• Extensive knowledge and hands on experience with Snowflake and its different components like User/Group, Data Store/ Warehouse management, External Stage/table, working with semi structured data, Snowpipe etc.
• Implement and manage CI/CD for migrating and deploying codes to higher environments with Snowflake codes.
• Proven experience with Snowflake Access control and authentication, data security, data sharing, working with VS Code extension for snowflake, replication, and failover, optimizing SQL, analytical ability to troubleshoot and debug on development and production issues quickly is key for success in this role.
• Proven technology champion in working with relational, Data warehouses databases, query authoring (SQL) as well as working familiarity with a variety of databases. 
• Highly Experienced in building and optimizing complex queries. Good with manipulating, processing, and extracting value from large, disconnected datasets.
• Your experience in handling big data sets and big data technologies will be an asset.
• Proven champion with in-depth knowledge of any one of the scripting languages: Python, SQL, Pyspark.

Primary responsibilities

• You will be an asset in our team bringing deep technical skills and capabilities to become a key part of projects defining the data journey in our company, keen to engage, network and innovate in collaboration with company wide teams.
• Collaborate with the data and analytics team to develop and maintain a data model and data governance infrastructure using a range of different storage technologies that enables optimal data storage and sharing using advanced methods.
• Support the development of processes and standards for data mining, data modeling and data protection.
• Design and implement continuous process improvements for automating manual processes and optimizing data delivery.
• Assess and report on the unique data needs of key stakeholders and troubleshoot any data-related technical issues through to resolution.
• Work to improve data models that support business intelligence tools, improve data accessibility and foster data-driven decision making.
• Ensure traceability of requirements from Data through testing and scope changes, to training and transition.
• Manage and lead technical design and development activities for implementation of large-scale data solutions in Snowflake to support multiple use cases (transformation, reporting and analytics, data monetization, etc.).
• Translate advanced business data, integration and analytics problems into technical approaches that yield actionable recommendations, across multiple, diverse domains; communicate results and educate others through design and build of insightful presentations.
• Exhibit strong knowledge of the Snowflake ecosystem and can clearly articulate the value proposition of cloud modernization/transformation to a wide range of stakeholders.

Relevant work experience

Bachelors in a Science, Technology, Engineering, Mathematics or Computer Science discipline or equivalent with 7+ Years of experience in enterprise-wide data warehousing, governance, policies, procedures, and implementation.

Aptitude for working with data, interpreting results, business intelligence and analytic best practices.

Business understanding

Good knowledge and understanding of Consumer and industrial products sector and IoT. 

Good functional understanding of solutions supporting business processes.

Skill Must have

• Snowflake 5+ years
• Overall different Data warehousing techs 5+ years
• SQL 5+ years
• Data warehouse designing experience 3+ years
• Experience with cloud and on-prem hybrid models in data architecture
• Knowledge of Data Governance and strong understanding of data lineage and data quality
• Programming & Scripting: Python, Pyspark
• Database technologies such as Traditional RDBMS (MS SQL Server, Oracle, MySQL, PostgreSQL)

Nice to have

• Demonstrated experience in modern enterprise data integration platforms such as Informatica
• AWS cloud services: S3, Lambda, Glue and Kinesis and API Gateway, EC2, EMR, RDS, Redshift and Kinesis
• Good understanding of Data Architecture approaches
• Experience in designing and building streaming data ingestion, analysis and processing pipelines using Kafka, Kafka Streams, Spark Streaming, Stream sets and similar cloud native technologies.
• Experience with implementation of operations concerns for a data platform such as monitoring, security, and scalability
• Experience working in DevOps, Agile, Scrum, Continuous Delivery and/or Rapid Application Development environments
• Building mock and proof-of-concepts across different capabilities/tool sets exposure
• Experience working with structured, semi-structured, and unstructured data, extracting information, and identifying linkages across disparate data sets

ABOUT EPISOURCE:

Episource has devoted more than a decade in building solutions for risk adjustment to measure healthcare outcomes. As one of the leading companies in healthcare, we have helped numerous clients optimize their medical records, data, analytics to enable better documentation of care for patients with chronic diseases.

The backbone of our consistent success has been our obsession with data and technology. At Episource, all of our strategic initiatives start with the question - how can data be “deployed”? Our analytics platforms and datalakes ingest huge quantities of data daily, to help our clients deliver services. We have also built our own machine learning and NLP platform to infuse added productivity and efficiency into our workflow. Combined, these build a foundation of tools and practices used by quantitative staff across the company.

What’s our poison you ask? We work with most of the popular frameworks and technologies like Spark, Airflow, Ansible, Terraform, Docker, ELK. For machine learning and NLP, we are big fans of keras, spacy, scikit-learn, pandas and numpy. AWS and serverless platforms help us stitch these together to stay ahead of the curve.

ABOUT THE ROLE:

We’re looking to hire someone to help scale Machine Learning and NLP efforts at Episource. You’ll work with the team that develops the models powering Episource’s product focused on NLP driven medical coding. Some of the problems include improving our ICD code recommendations, clinical named entity recognition, improving patient health, clinical suspecting and information extraction from clinical notes.

This is a role for highly technical data engineers who combine outstanding oral and written communication skills, and the ability to code up prototypes and productionalize using a large range of tools, algorithms, and languages. Most importantly they need to have the ability to autonomously plan and organize their work assignments based on high-level team goals.

You will be responsible for setting an agenda to develop and ship data-driven architectures that positively impact the business, working with partners across the company including operations and engineering. You will use research results to shape strategy for the company and help build a foundation of tools and practices used by quantitative staff across the company.

During the course of a typical day with our team, expect to work on one or more projects around the following;

1. Create and maintain optimal data pipeline architectures for ML

2. Develop a strong API ecosystem for ML pipelines

3. Building CI/CD pipelines for ML deployments using Github Actions, Travis, Terraform and Ansible

4. Responsible to design and develop distributed, high volume, high-velocity multi-threaded event processing systems

5. Knowledge of software engineering best practices across the development lifecycle, coding standards, code reviews, source management, build processes, testing, and operations  

6. Deploying data pipelines in production using Infrastructure-as-a-Code platforms

7. Designing scalable implementations of the models developed by our Data Science teams  

8. Big data and distributed ML with PySpark on AWS EMR, and more!

BASIC REQUIREMENTS 

1.  Bachelor’s degree or greater in Computer Science, IT or related fields
   
   

2.  Minimum of 5 years of experience in cloud, DevOps, MLOps & data projects
   
   

3. Strong experience with bash scripting, unix environments and building scalable/distributed systems
   
   

4. Experience with automation/configuration management using Ansible, Terraform, or equivalent
   
   

5. Very strong experience with AWS and Python
   
   

6. Experience building CI/CD systems
   
   

7. Experience with containerization technologies like Docker, Kubernetes, ECS, EKS or equivalent

8. Ability to build and manage application and performance monitoring processes

We are looking for a Data Analyst that oversees organisational data analytics. This will require you to design and help implement the data analytics platform that will keep the organisation running. The team will be the go-to for all data needs for the app and we are looking for a self-starter who is hands on and yet able to abstract problems and anticipate data requirements.
This person should be very strong technical data analyst who can design and implement data systems on his own. Along with him, he also needs to be proficient in business reporting and should have keen interest in provided data needed for business.

Tools familiarity:  SQL, Python, Mix panel, Metabase, Google Analytics,  Clever Tap, App Analytics

Responsibilities

• Processes and frameworks for metrics, analytics, experimentation and user insights, lead the data analytics team
• Metrics alignment across teams to make them actionable and promote accountability
• Data based frameworks for assessing and strengthening Product Market Fit
• Identify viable growth strategies through data and experimentation
• Experimentation for product optimisation and understanding user behaviour
• Structured approach towards deriving user insights, answer questions using data
• This person needs to closely work with Technical and Business teams to get this implemented.

Skills

• 4 to 6 years at a relevant role in data analytics in a Product Oriented company
• Highly organised, technically sound & good at communication
• Ability to handle & build for cross functional data requirements / interactions with teams
• Great with Python, SQL
• Can build, mentor a team
• Knowledge of key business metrics like cohort, engagement cohort, LTV, ROAS, ROE

Eligibility

BTech or MTech in Computer Science/Engineering from a Tier1, Tier2 colleges

Good knowledge on Data Analytics, Data Visualization tools. A formal certification would be added advantage.

We are more interested in what you CAN DO than your location, education, or experience levels.

Send us your code samples / GitHub profile / published articles if applicable.

Big Data Engineer: 5+ yrs.
Immediate Joiner

• Expertise in building AWS Data Engineering pipelines with AWS Glue -> Athena -> Quick sight
• Experience in developing lambda functions with AWS Lambda
• Expertise with Spark/PySpark – Candidate should be hands on with PySpark code and should be able to do transformations with Spark
• Should be able to code in Python and Scala.
• Snowflake experience will be a plus
• We can start keeping Hadoop and Hive requirements as good to have or understanding of is enough rather than keeping it as a desirable requirement.

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.

What's the role?

Your role as a Principal Engineer will involve working with various team. As a principal engineer, will need full knowledge of the software development lifecycle and Agile methodologies. You will demonstrate multi-tasking skills under tight deadlines and constraints. You will regularly contribute to the development of work products (including analyzing, designing, programming, debugging, and documenting software) and may work with customers to resolve challenges and respond to suggestions for improvements and enhancements. You will setup the standard and principal for the product he/she drives.

• Setup coding practice, guidelines & quality of the software delivered.
• Determines operational feasibility by evaluating analysis, problem definition, requirements, solution development, and proposed solutions.
• Documents and demonstrates solutions by developing documentation, flowcharts, layouts, diagrams, charts, code comments and clear code.
• Prepares and installs solutions by determining and designing system specifications, standards, and programming.
• Improves operations by conducting systems analysis; recommending changes in policies and procedures.
• Updates job knowledge by studying state-of-the-art development tools, programming techniques, and computing equipment; participating in educational opportunities; reading professional publications; maintaining personal networks; participating in professional organizations.
• Protects operations by keeping information confidential.
• Develops software solutions by studying information needs; conferring with users; studying systems flow, data usage, and work processes; investigating problem areas; following the software development lifecycle. Who are you? You are a go-getter, with an eye for detail, strong problem-solving and debugging skills, and having a degree in BE/MCA/M.E./ M Tech degree or equivalent degree from reputed college/university.

Essential Skills / Experience:

• 10+ years of engineering experience
• Experience in designing and developing high volume web-services using API protocols and data formats
• Proficient in API modelling languages and annotation
• Proficient in Java programming
• Experience with Scala programming
• Experience with ETL systems
• Experience with Agile methodologies
• Experience with Cloud service & storage
• Proficient in Unix/Linux operating systems
• Excellent oral and written communication skills Preferred:
• Functional programming languages (Scala, etc)
• Scripting languages (bash, Perl, Python, etc)
• Amazon Web Services (Redshift, ECS etc)