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Job Description
Structured overview of role & requirementsAbout This Role
Design, build, and maintain scalable ETL/ELT data pipelines and platforms primarily on AWS using services like Glue, Lambda, Redshift, and Kinesis.
Manage and optimize large structured and unstructured data stores, ensuring data security, governance, and compliance (e.g., GDPR) through AWS Lake Formation, IAM roles, and encryption.
Monitor pipeline health and performance using CloudWatch and CloudTrail, implement CI/CD using CloudFormation or Terraform, and collaborate in Agile teams to deliver data solutions aligned with business needs.
Minimum Requirements
3+ years of professional data engineering or software engineering experience focused on data engineering.
Proficiency with AWS data services (S3, Glue, Redshift, Athena, EMR, Lambda, CloudFormation, Kinesis, DynamoDB, Lake Formation) and big data tools (Apache Spark, Databricks, Hadoop, Kafka).
Experience with Python, SQL, and Scala programming languages and DevOps practices including Git, CI/CD, CloudFormation or Terraform.
Bachelor's degree or equivalent experience in Engineering or Computer Science.
Ideal Candidate Profile
Experienced in delivering complex, production-grade data pipelines with strong data security and governance mindset.
Proven ability to translate ambiguous business requirements into scalable and governed data solutions in Agile, cross-functional product environments.
Comfortable managing very large data warehouses or lakes, optimizing ETL workflows, and operating within AWS infrastructure and security best practices.