Aws Data Engineer

AWS Data Engineer

Key Responsibilities

• Design and implement

  scalable, secure, and high-performance

  data architectures

  to support enterprise data warehousing and analytics.

• Develop and maintain ETL/ELT pipelines

  leveraging AWS services such as

  Glue, Redshift, Lambda, DMS, and S3

  .
• Utilize

  Python, PySpark, and SQL

  to build data transformation and ingestion workflows.
• Optimize data flows and query performance for high-volume, real-time, and batch data processing.
• Implement and maintain

  data quality, validation, and reconciliation frameworks

  to ensure accuracy and reliability of data.
• Work closely with Data Architects, Analysts, and Product Teams to understand business needs and translate them into data-driven solutions.
• Apply

  data warehousing best practices

  , including star/snowflake schema design, partitioning, indexing, and performance tuning.
• Participate in

  CI/CD workflows

  and use

  version control systems

  (Git, CodeCommit) to ensure smooth data pipeline deployment and versioning.
• Monitor, troubleshoot, and enhance existing pipelines for performance, scalability, and cost optimization.

Required Qualifications

• 5+ years

  of experience as a

  Data Engineer

  , with a strong focus on

  AWS-based data platforms

  .
• Deep understanding of

  AWS data ecosystem

  , including

  Redshift, Glue, S3, DMS, Lambda

  .
• Proficiency in

  Python, PySpark, and SQL

  for data processing and transformation.
• Strong foundation in

  data warehousing concepts and design techniques

  (e.g., dimensional modeling, normalization, denormalization).
• Experience with

  workflow orchestration

  tools like

  Apache Airflow or AWS Managed Airflow

  .
• Familiarity with

  Terraform

  and

  CI/CD pipelines

  for automating data infrastructure deployments.
• Hands-on experience with

  Git-based version control

  and collaborative development practices.
• Proven experience working with

  JSON and other semi-structured data formats.

• Excellent analytical thinking, problem-solving, and debugging skills.
• Strong written and verbal communication skills to collaborate with cross-functional stakeholders.

Soft Skills

• Strong ownership mindset and ability to work independently in fast-paced environments.
• Collaborative attitude and willingness to mentor junior team members.
• Attention to detail with a focus on delivering high-quality, production-ready data solutions.