AWS Data Engineer (Redshift)

Role:

Location:

Industry Exposure:

About the Role

AWS Data Engineer

Key Responsibilities

• Design, develop, and optimize

  data ingestion pipelines, ETL/ELT workflows

  , and transformations across ODS/EDW layers.
• Build and maintain

  data models (Star/Snowflake, 3NF, time-series)

  in Redshift to support operational and analytical workloads.
• Work extensively with

  AWS Redshift

  (Spectrum, RA3, WLM, Query Tuning, Distribution/Sort Keys).
• Leverage AWS-native services:

  S3, Glue, Athena, Aurora, Step Functions, Lambda, Lake Formation

  for processing, storage, and orchestration.
• Ensure

  performance optimization, partitioning, compaction, and cost efficiency

  .
• Write

  reusable, well-tested code in Python/Java

  for transformations and orchestration.
• Monitor and troubleshoot jobs using

  CloudWatch, Glue metrics, Redshift monitoring tools

  .
• Ensure

  SOX compliance, governance, and access controls

  .
• Collaborate with architects, analysts, and business teams to deliver

  high-quality, governed datasets

  .

Required Qualifications

• 5+ years of experience

  in data engineering with strong exposure to

  AWS and Redshift

  .
• Proven experience in

  designing and optimizing Redshift data warehouses

  .
• Strong expertise in

  data modeling

  (Star/Snowflake, ODS, EDW).
• Hands-on experience with

  AWS Glue, S3, Athena, Aurora, Step Functions, Lambda

  .
• Strong coding skills in

  Python and/or Java

  (frameworks, libraries, reusability).
• Familiarity with

  CI/CD (Git, CodePipeline, Terraform/CloudFormation)

  .
• Good understanding of

  batch vs. streaming

  , event-driven patterns, and data decoupling.

Preferred Qualifications

• AWS Certified

  Data Analytics Specialty

  (or actively pursuing).
• Experience with

  Snowflake, Databricks, or Redshift Spectrum

  .
• Familiarity with

  Kafka, Kinesis, or streaming pipelines

  .
• Exposure to

  Airflow, dbt, or other orchestration tools

  .
• Prior experience in

  SOX-compliant architectures, data governance, and lineage

  .