Senior Data Engineer

Key Responsibilities:

• Lead the design, development, and optimization of large-scale, reliable, and secure data pipelines and data lake architecture on AWS.

• Architect and implement end-to-end data solutions, including data ingestion, storage, transformation, and analytics using AWS services (Glue, Redshift, S3, Lambda, EMR, Kinesis, Athena, RDS, etc.).

• Mentor and guide a team of data engineers, conducting code reviews and fostering best practices in data engineering and cloud architecture.

• Collaborate with data scientists, analysts, and business stakeholders to translate requirements into scalable and maintainable solutions.

• Oversee migration of data from legacy systems to AWS-based data lakes and data warehouses.

• Develop and enforce standards for data quality, security, and governance.

• Drive the adoption of DevOps, CI/CD, and infrastructure-as-code practices within the data engineering team.

• Ensure solutions are cost-effective, performant, and aligned with enterprise data strategy.

• Stay current with advancements in AWS technologies and data engineering trends and evaluate new tools and frameworks for potential adoption.

• Troubleshoot complex data issues and provide technical leadership in problem resolution.

 Required Qualifications:

• Bachelor''s or Master''s degree in Computer Science, Engineering, or a related field.

• 10+ years of experience in data engineering, with at least 3 years in technical leadership or lead engineer role.

• Extensive hands-on experience with AWS data services (Glue, Redshift, S3, Lambda, EMR/Spark, Kinesis, Athena, RDS, API Gateway, etc.).

• Proficient in programming languages such as Python and SQL; experience with Shell scripting and Scala is a plus.

• Strong experience designing, implementing, and managing data lakes, data warehouses, and data ingestion pipelines on AWS.

• Proven experience with ETL/ELT processes, data modeling, and big data frameworks.

• Demonstrated ability to lead, mentor, and coach engineers in a collaborative team environment.

• Experience with DevOps practices, CI/CD pipelines, and infrastructure-as-code tools (e.g., CloudFormation, Terraform).

• Excellent problem-solving, communication, and organizational skills.

• AWS Solutions Architect or AWS Data Engineer certification.

• Experience with real-time streaming technologies.

• Knowledge of data governance, compliance, and security best practices.

• Familiarity with Lakehouse architecture and modern data platforms.