Data Engineer – AWS (Glue, Athena, Redshift) & Informatica

Job Summary

We are seeking a skilled Data Engineer with strong expertise in AWS-native data services and Informatica to design, build, and optimize scalable data pipelines. The ideal candidate will work with large volumes of structured and semi-structured data to support analytics, reporting, and downstream business intelligence platforms within a regulated enterprise environment.

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines using AWS Glue and Informatica (PowerCenter / IDMC / IICS)
• Build, optimize, and manage analytical datasets in Amazon Redshift
• Enable data exploration and ad-hoc querying using Amazon Athena
• Ingest data from diverse sources including RDBMS, flat files, APIs, and cloud storage into AWS platforms
• Ensure data quality through validation, reconciliation, and monitoring processes
• Implement performance tuning strategies including partitioning, indexing, and compression for Redshift and Athena
• Work with structured and semi-structured data formats such as CSV, JSON, Parquet, and Avro in Amazon S3
• Collaborate with BI, analytics, and data science teams to deliver curated, high-quality datasets
• Implement logging, monitoring, and error-handling mechanisms for data pipelines
• Ensure adherence to security, governance, and compliance standards (PII handling, encryption, IAM, auditability)
• Support production issues, perform root cause analysis, and drive continuous improvements

Required Skills & Qualifications

Core Technical Skills

• Strong hands-on experience with AWS Glue (ETL jobs, Crawlers, Data Catalog)
• Experience with Amazon Athena for querying large datasets in S3
• Solid experience with Amazon Redshift (schema design, performance tuning, WLM, distribution strategies)
• Strong experience with Informatica (PowerCenter or Intelligent Data Management Cloud – IICS/IDMC)
• Advanced SQL skills (complex joins, window functions, query optimization)
• Hands-on experience with Python and/or Spark (PySpark)
• Strong understanding of data warehousing concepts (fact/dimension modeling, star/snowflake schemas)

Cloud & Data Ecosystem

• Experience with Amazon S3, IAM, and CloudWatch
• Understanding of data lake and lakehouse architectures
• Experience with batch and near real-time data processing
• Familiarity with CI/CD pipelines for data workflows

Preferred / Nice-to-Have Skills

• Experience in banking, financial services, or insurance domains
• Exposure to AWS services such as Step Functions, Lambda, and EMR
• Knowledge of data governance, metadata management, and lineage
• Experience with Informatica Cloud (IDMC) advanced capabilities
• Familiarity with Agile / Scrum methodologies
• Experience working in regulatory and compliance-driven environments