AWS Data Engineer
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Job Description
This role requires strong data Engineering& analysis expertise across SQL, Data modelling, DBT, Airflow, and Lakehouse/data lake architecture, with hands-on experience querying large-scale distributed datasets directly from data lakes.
Banking/financial services experience, exposure to ledger/ transactional/ regulatory data, support for migration/modernization program, familiarity, with data governance / metadata. regulatory controls.
Key Responsibilities
· Design, develop, and maintain scalable data pipelines using PySpark on AWS. · Build and orchestrate ETL/ELT workflows using AWS Glue and AWS Step Functions. · Develop serverless applications and automation using AWS Lambda.
· Write clean, efficient, and maintainable Python/PySpark code following engineering best practices. · Provision and manage cloud infrastructure using Terraform (Infrastructure as Code). · Implement and maintain CI/CD pipelines to automate code deployment, testing, and infrastructure changes.
· Monitor, troubleshoot, and optimize data pipelines for performance, reliability, and cost efficiency. · Collaborate with business stakeholders to deliver data solutions. · Follow DevOps, security, and coding standards throughout the engagement.
Required Skills
· Strong hands-on experience with PySpark and Python for data engineering. · Experience developing ETL pipelines using AWS Glue. · Proficiency with AWS Step Functions for workflow orchestration. · Experience building serverless solutions using AWS Lambda.
· Hands-on experience with Terraform for Infrastructure as Code (IaC). · Experience implementing CI/CD pipelines using tools such as GitLab, GitHub Actions, Jenkins, or similar. · Good understanding of AWS services, data lakes, IAM, S3, CloudWatch, and monitoring.
Required Skills
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