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Technical Skills:
- Ability to understand and translate business requirements into design.
- Proficient in AWS infrastructure components such as S3, IAM, VPC, EC2, and Redshift.
- Experience in creating ETL jobs using Python/PySpark.
- Proficiency in creating AWS Lambda functions for event-based jobs.
- Knowledge of automating ETL processes using AWS Step Functions.
- Competence in building data warehouses and loading data into them.
Responsibilities:
- Understand business requirements and translate them into design.
- Assess AWS infrastructure needs for development work.
- Develop ETL jobs using Python/PySpark to meet requirements.
- Implement AWS Lambda for event-based tasks.
- Automate ETL processes using AWS Step Functions.
- Build data warehouses and manage data loading.
- Engage with customers and stakeholders to articulate the benefits of proposed solutions and frameworks.
- Mandatory - Hands on experience in Python and PySpark.
- Build pySpark applications using Spark Dataframes in Python using Jupyter notebook and PyCharm(IDE).
- Worked on optimizing spark jobs that processes huge volumes of data.
- Hands on experience in version control tools like Git.
- Worked on Amazon’s Analytics services like Amazon EMR, Lambda function etc
- Worked on Amazon’s Compute services like Amazon Lambda, Amazon EC2 and Amazon’s Storage service like S3 and few other services like SNS.
- Experience/knowledge of bash/shell scripting will be a plus.
- Experience in working with fixed width, delimited , multi record file formats etc.
- Hands on experience in tools like Jenkins to build, test and deploy the applications
- Awareness of Devops concepts and be able to work in an automated release pipeline environment.
- Excellent debugging skills.
at TSG Global Services Private Limited
Greetings !!!
Looking Urgently !!!
Exp-Min 10 Years
Location-Delhi
Sal-nego
Role
AWS Data Migration Consultant
Provide Data Migration strategy, expert review and guidance on Data Migration from onprem to AWS infrastructure that includes AWS Fargate, PostgreSQL, DynamoDB. This includes review and SME inputs on:
· Data migration plan, architecture, policies, procedures
· Migration testing methodologies
· Data integrity, consistency, resiliency.
· Performance and Scalability
· Capacity planning
· Security, access control, encryption
· DB replication and clustering techniques
· Migration risk mitigation approaches
· Verification and integrity testing, reporting (Record and field level verifications)
· Schema consistency and mapping
· Logging, error recovery
· Dev-test, staging and production artifact promotions and deployment pipelines
· Change management
· Backup, DR approaches and best practices.
Qualifications
- Worked on mid to large scale data migration projects, specifically from on-prem to AWS, preferably in BFSI domain
- Deep expertise in AWS Redshift, PostgreSQL, DynamoDB from data management, performance, scalability and consistency standpoint
- Strong knowledge of AWS Cloud architecture and components, solutions, well architected frameworks
- Expertise in SQL and DB performance related aspects
- Solution Architecture work for enterprise grade BFSI applications
- Successful track record of defining and implementing data migration strategies
- Excellent communication and problem solving skills
- 10+ Yrs experience in Technology, at least 4+yrs in AWS and DBA/DB Management/Migration related work
- Bachelors degree or higher in Engineering or related field
Job Responsibilities
- Design, build & test ETL processes using Python & SQL for the corporate data warehouse
- Inform, influence, support, and execute our product decisions
- Maintain advertising data integrity by working closely with R&D to organize and store data in a format that provides accurate data and allows the business to quickly identify issues.
- Evaluate and prototype new technologies in the area of data processing
- Think quickly, communicate clearly and work collaboratively with product, data, engineering, QA and operations teams
- High energy level, strong team player and good work ethic
- Data analysis, understanding of business requirements and translation into logical pipelines & processes
- Identification, analysis & resolution of production & development bugs
- Support the release process including completing & reviewing documentation
- Configure data mappings & transformations to orchestrate data integration & validation
- Provide subject matter expertise
- Document solutions, tools & processes
- Create & support test plans with hands-on testing
- Peer reviews of work developed by other data engineers within the team
- Establish good working relationships & communication channels with relevant departments
Skills and Qualifications we look for
- University degree 2.1 or higher (or equivalent) in a relevant subject. Master’s degree in any data subject will be a strong advantage.
- 4 - 6 years experience with data engineering.
- Strong coding ability and software development experience in Python.
- Strong hands-on experience with SQL and Data Processing.
- Google cloud platform (Cloud composer, Dataflow, Cloud function, Bigquery, Cloud storage, dataproc)
- Good working experience in any one of the ETL tools (Airflow would be preferable).
- Should possess strong analytical and problem solving skills.
- Good to have skills - Apache pyspark, CircleCI, Terraform
- Motivated, self-directed, able to work with ambiguity and interested in emerging technologies, agile and collaborative processes.
- Understanding & experience of agile / scrum delivery methodology
AWS Glue Developer
Work Experience: 6 to 8 Years
Work Location: Noida, Bangalore, Chennai & Hyderabad
Must Have Skills: AWS Glue, DMS, SQL, Python, PySpark, Data integrations and Data Ops,
Job Reference ID:BT/F21/IND
Job Description:
Design, build and configure applications to meet business process and application requirements.
Responsibilities:
7 years of work experience with ETL, Data Modelling, and Data Architecture Proficient in ETL optimization, designing, coding, and tuning big data processes using Pyspark Extensive experience to build data platforms on AWS using core AWS services Step function, EMR, Lambda, Glue and Athena, Redshift, Postgres, RDS etc and design/develop data engineering solutions. Orchestrate using Airflow.
Technical Experience:
Hands-on experience on developing Data platform and its components Data Lake, cloud Datawarehouse, APIs, Batch and streaming data pipeline Experience with building data pipelines and applications to stream and process large datasets at low latencies.
➢ Enhancements, new development, defect resolution and production support of Big data ETL development using AWS native services.
➢ Create data pipeline architecture by designing and implementing data ingestion solutions.
➢ Integrate data sets using AWS services such as Glue, Lambda functions/ Airflow.
➢ Design and optimize data models on AWS Cloud using AWS data stores such as Redshift, RDS, S3, Athena.
➢ Author ETL processes using Python, Pyspark.
➢ Build Redshift Spectrum direct transformations and data modelling using data in S3.
➢ ETL process monitoring using CloudWatch events.
➢ You will be working in collaboration with other teams. Good communication must.
➢ Must have experience in using AWS services API, AWS CLI and SDK
Professional Attributes:
➢ Experience operating very large data warehouses or data lakes Expert-level skills in writing and optimizing SQL Extensive, real-world experience designing technology components for enterprise solutions and defining solution architectures and reference architectures with a focus on cloud technology.
➢ Must have 6+ years of big data ETL experience using Python, S3, Lambda, Dynamo DB, Athena, Glue in AWS environment.
➢ Expertise in S3, RDS, Redshift, Kinesis, EC2 clusters highly desired.
Qualification:
➢ Degree in Computer Science, Computer Engineering or equivalent.
Salary: Commensurate with experience and demonstrated competence
consulting & implementation services in the area of Oil & Gas, Mining and Manufacturing Industry
- Data Engineer
Required skill set: AWS GLUE, AWS LAMBDA, AWS SNS/SQS, AWS ATHENA, SPARK, SNOWFLAKE, PYTHON
Mandatory Requirements
- Experience in AWS Glue
- Experience in Apache Parquet
- Proficient in AWS S3 and data lake
- Knowledge of Snowflake
- Understanding of file-based ingestion best practices.
- Scripting language - Python & pyspark
CORE RESPONSIBILITIES
- Create and manage cloud resources in AWS
- Data ingestion from different data sources which exposes data using different technologies, such as: RDBMS, REST HTTP API, flat files, Streams, and Time series data based on various proprietary systems. Implement data ingestion and processing with the help of Big Data technologies
- Data processing/transformation using various technologies such as Spark and Cloud Services. You will need to understand your part of business logic and implement it using the language supported by the base data platform
- Develop automated data quality check to make sure right data enters the platform and verifying the results of the calculations
- Develop an infrastructure to collect, transform, combine and publish/distribute customer data.
- Define process improvement opportunities to optimize data collection, insights and displays.
- Ensure data and results are accessible, scalable, efficient, accurate, complete and flexible
- Identify and interpret trends and patterns from complex data sets
- Construct a framework utilizing data visualization tools and techniques to present consolidated analytical and actionable results to relevant stakeholders.
- Key participant in regular Scrum ceremonies with the agile teams
- Proficient at developing queries, writing reports and presenting findings
- Mentor junior members and bring best industry practices
QUALIFICATIONS
- 5-7+ years’ experience as data engineer in consumer finance or equivalent industry (consumer loans, collections, servicing, optional product, and insurance sales)
- Strong background in math, statistics, computer science, data science or related discipline
- Advanced knowledge one of language: Java, Scala, Python, C#
- Production experience with: HDFS, YARN, Hive, Spark, Kafka, Oozie / Airflow, Amazon Web Services (AWS), Docker / Kubernetes, Snowflake
- Proficient with
- Data mining/programming tools (e.g. SAS, SQL, R, Python)
- Database technologies (e.g. PostgreSQL, Redshift, Snowflake. and Greenplum)
- Data visualization (e.g. Tableau, Looker, MicroStrategy)
- Comfortable learning about and deploying new technologies and tools.
- Organizational skills and the ability to handle multiple projects and priorities simultaneously and meet established deadlines.
- Good written and oral communication skills and ability to present results to non-technical audiences
- Knowledge of business intelligence and analytical tools, technologies and techniques.
Familiarity and experience in the following is a plus:
- AWS certification
- Spark Streaming
- Kafka Streaming / Kafka Connect
- ELK Stack
- Cassandra / MongoDB
- CI/CD: Jenkins, GitLab, Jira, Confluence other related tools
Who Are We
A research-oriented company with expertise in computer vision and artificial intelligence, at its core, Orbo is a comprehensive platform of AI-based visual enhancement stack. This way, companies can find a suitable product as per their need where deep learning powered technology can automatically improve their Imagery.
ORBO's solutions are helping BFSI, beauty and personal care digital transformation and Ecommerce image retouching industries in multiple ways.
WHY US
- Join top AI company
- Grow with your best companions
- Continuous pursuit of excellence, equality, respect
- Competitive compensation and benefits
You'll be a part of the core team and will be working directly with the founders in building and iterating upon the core products that make cameras intelligent and images more informative.
To learn more about how we work, please check out
Description:
We are looking for a computer vision engineer to lead our team in developing a factory floor analytics SaaS product. This would be a fast-paced role and the person will get an opportunity to develop an industrial grade solution from concept to deployment.
Responsibilities:
- Research and develop computer vision solutions for industries (BFSI, Beauty and personal care, E-commerce, Defence etc.)
- Lead a team of ML engineers in developing an industrial AI product from scratch
- Setup end-end Deep Learning pipeline for data ingestion, preparation, model training, validation and deployment
- Tune the models to achieve high accuracy rates and minimum latency
- Deploying developed computer vision models on edge devices after optimization to meet customer requirements
Requirements:
- Bachelor’s degree
- Understanding about depth and breadth of computer vision and deep learning algorithms.
- 4+ years of industrial experience in computer vision and/or deep learning
- Experience in taking an AI product from scratch to commercial deployment.
- Experience in Image enhancement, object detection, image segmentation, image classification algorithms
- Experience in deployment with OpenVINO, ONNXruntime and TensorRT
- Experience in deploying computer vision solutions on edge devices such as Intel Movidius and Nvidia Jetson
- Experience with any machine/deep learning frameworks like Tensorflow, and PyTorch.
- Proficient understanding of code versioning tools, such as Git
Our perfect candidate is someone that:
- is proactive and an independent problem solver
- is a constant learner. We are a fast growing start-up. We want you to grow with us!
- is a team player and good communicator
What We Offer:
- You will have fun working with a fast-paced team on a product that can impact the business model of E-commerce and BFSI industries. As the team is small, you will easily be able to see a direct impact of what you build on our customers (Trust us - it is extremely fulfilling!)
- You will be in charge of what you build and be an integral part of the product development process
- Technical and financial growth!
We are looking for a Senior Data Engineer to join the Customer Innovation team, who will be responsible for acquiring, transforming, and integrating customer data onto our Data Activation Platform from customers’ clinical, claims, and other data sources. You will work closely with customers to build data and analytics solutions to support their business needs, and be the engine that powers the partnership that we build with them by delivering high-fidelity data assets.
In this role, you will work closely with our Product Managers, Data Scientists, and Software Engineers to build the solution architecture that will support customer objectives. You'll work with some of the brightest minds in the industry, work with one of the richest healthcare data sets in the world, use cutting-edge technology, and see your efforts affect products and people on a regular basis. The ideal candidate is someone that
- Has healthcare experience and is passionate about helping heal people,
- Loves working with data,
- Has an obsessive focus on data quality,
- Is comfortable with ambiguity and making decisions based on available data and reasonable assumptions,
- Has strong data interrogation and analysis skills,
- Defaults to written communication and delivers clean documentation, and,
- Enjoys working with customers and problem solving for them.
A day in the life at Innovaccer:
- Define the end-to-end solution architecture for projects by mapping customers’ business and technical requirements against the suite of Innovaccer products and Solutions.
- Measure and communicate impact to our customers.
- Enabling customers on how to activate data themselves using SQL, BI tools, or APIs to solve questions they have at speed.
What You Need:
- 4+ years of experience in a Data Engineering role, a Graduate degree in Computer Science, Statistics, Informatics, Information Systems, or another quantitative field.
- 4+ years of experience working with relational databases like Snowflake, Redshift, or Postgres.
- Intermediate to advanced level SQL programming skills.
- Data Analytics and Visualization (using tools like PowerBI)
- The ability to engage with both the business and technical teams of a client - to document and explain technical problems or concepts in a clear and concise way.
- Ability to work in a fast-paced and agile environment.
- Easily adapt and learn new things whether it’s a new library, framework, process, or visual design concept.
What we offer:
- Industry certifications: We want you to be a subject matter expert in what you do. So, whether it’s our product or our domain, we’ll help you dive in and get certified.
- Quarterly rewards and recognition programs: We foster learning and encourage people to take risks. We recognize and reward your hard work.
- Health benefits: We cover health insurance for you and your loved ones.
- Sabbatical policy: We encourage people to take time off and rejuvenate, learn new skills, and pursue their interests so they can generate new ideas with Innovaccer.
- Pet-friendly office and open floor plan: No boring cubicles.
As a Data Science Lead, you will be working on creating industry first analytical and propensity models to
help discover the information hidden in vast amounts of data, and make smarter decisions to deliver
even better customer experience. Your primary focus will be in applying data mining techniques, doing
statistical analysis, and building high quality prediction systems integrated with our products.
➢ Working with business and leadership teams to gathering and analyse structured and unstructured data
➢ Data mining using state-of-the-art methods
➢ Enhancing data collection procedures to include information that is relevant for building analytic
systems
➢ Processing, cleansing, and verifying the integrity of data used for analysis
➢ Doing ad-hoc analysis and presenting results in a clear manner
➢ Creating automated anomaly detection systems and constant tracking of its performance
➢ Creation and evolution of an efficient BI pipeline into a multi-faceted pipeline to support various
modelling needs.
What we are looking for:
➢ 5-8 years of relevant experience, preferably in financial services industry.
➢ A bachelors / master’s degree in the field of Statistics, Mathematics, Computer Science or
Management from Tier 1 Institutes.
➢ Data warehousing experience will be a plus.
➢ Good conceptual understanding of statistics and probability.
➢ Experience in developing dashboards and reports using BI tools.