Data Engineer

We’re looking for a 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.

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

4–7 years of experience in data engineering , with 3+ years on AWS platforms

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 H adoop / HDFS in hybrid or legacy environments