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About the role
We're looking for a Senior Data Engineer to design, build, and scale modern data platforms on AWS. You'll work with Python, Spark, DBT, and AWS-native services in an Agile environment to deliver scalable, secure, and high-performance data solutions. Experience: 7–10 years of experience in data engineering, with 4+ years on AWS platforms What you'll do Develop and optimize ETL/ELT pipelines with Python, DBT, and AWS services (Data Ops Live). Build and manage S3-based data lakes using modern data formats (Parquet, ORC, Iceberg). Deliver end-to-end data solutions with Glue, EMR, Lambda, Redshift, and Athena. Implement strong metadata, governance, and security using Glue Data Catalog, Lake Formation, IAM, and KMS. Orchestrate workflows with Airflow, Step Functions, or AWS-native tools. Ensure reliability and automation with CloudWatch, CloudTrail, CodePipeline, and Terraform. Collaborate with analysts and data scientists to deliver business insights in an Agile setting. Required Skills & Experience Strong in Python (incl. AWS SDKs), DBT, SQL, and Spark Proven expertise with AWS data stack (S3, Glue, EMR, Redshift, Athena, Lambda) Hands-on experience with workflow orchestration (Airflow/Step Functions) Familiarity with data lake formats (Parquet, ORC, Iceberg) and DevOps practices (Terraform, CI/CD) Solid understanding of data governance & security best practices Bonus Exposure to Data Mesh principles and platforms like Data.World Familiarity with Hadoop/HDFS in hybrid or legacy environments
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