Data Engineer

We’re looking for

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