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.
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
* 7–10 years of experience in
data engineering
, with 4+ 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