Data Engineer

3 weeks ago

Salem, India Staffingine LLC Full time

Data Engineer India, Remote Full Time /Contract # of Positions - 3 Job Summary The Data Engineer will be responsible for designing, developing, and optimizing scalable data pipelines and cloud-based data solutions. This role requires strong Python programming skills, expertise in ETL/ELT processes, and deep hands-on experience with AWS cloud services such as S3, Glue, Lambda, Redshift, Kinesis, and DynamoDB. The ideal candidate will excel in building serverless data architectures, designing efficient data models, and ensuring robust pipeline performance through monitoring and optimization. The position is remote within India and open for both full-time and contract engagements. Key Skills Data Engineering & Pipelines - ETL/ELT pipeline development using Python - Data extraction, transformation, and loading into data lakes/warehouses - Workflow orchestration and automation - Real-time and batch data processing AWS Cloud Expertise - S3, Glue, Lambda, Redshift, Aurora - Kinesis (real-time streaming) - DynamoDB (NoSQL databases) - AWS serverless architecture design - Integration of AWS managed services for data workflows Serverless & Automation - Building event-driven pipelines using AWS Lambda - Serverless compute optimization - Automated triggering and orchestration of data processes Data Modeling - Designing schemas for relational databases (OLTP/OLAP) - NoSQL data modeling and storage optimization - Understanding of normalization, partitioning, indexing Monitoring & Optimization - AWS monitoring tools (CloudWatch, CloudTrail) - Pipeline performance tuning - Cost optimization across cloud resources Collaboration & Communication - Cross-functional collaboration with analysts, data scientists, and engineering teams - Strong problem-solving, documentation, and communication skills Minimum Qualifications - Bachelor’s degree in Computer Science, Information Technology, Engineering, or related field (preferred). - Strong hands-on experience with Python for data engineering tasks. - Deep understanding of AWS cloud services used for data storage, streaming, ETL, and serverless compute. - Experience designing and implementing ETL/ELT pipelines. - Solid understanding of relational and NoSQL data modeling concepts. Professional Experience Requirements - Proven experience building scalable data pipelines using Python. - Experience extracting and transforming data from diverse sources into cloud-based environments. - Hands-on experience with AWS services such as S3, Glue ETL, Lambda, Redshift/Aurora, Kinesis, and DynamoDB. - Demonstrated ability to design and implement serverless architectures. - Experience creating event-driven workflows using Lambda and other AWS triggers. - Strong experience in monitoring, debugging, and optimizing cloud-based data workflows. - Experience collaborating across data science, analytics, and engineering teams to deliver complete data solutions.

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