Senior AWS Data Engineer

Job Title: Senior AWS Data Engineer

Experience: 12+ Years

Location: Dallas, TX

Job Summary:

We are seeking a highly experienced Senior AWS Data Engineer with 12+ years of expertise in designing, building, and optimizing large-scale data platforms on AWS. The ideal candidate will have deep hands-on experience with modern data engineering tools, cloud-native architectures, real-time/streaming pipelines, and enterprise data warehousing. This role involves leading technical design, driving best practices, and collaborating closely with cross-functional teams to enable scalable, secure, and high-performance data solutions.

Key Responsibilities:

Architect, design, and implement end-to-end data pipelines and ETL/ELT frameworks on AWS.

Build scalable data ingestion, processing, and storage solutions using services such as AWS Glue, Lambda, Step Functions, EMR, Kinesis, Redshift, S3, Athena, and API Gateway.

Develop and maintain data lakes, data warehouses, and analytical datasets to support BI, data science, and operational workloads.

Lead the modernization of legacy data systems into cloud-native AWS architectures.

Optimize data pipelines for scalability, performance, and cost efficiency.

Implement robust data quality, governance, lineage, and security mechanisms following industry best practices.

Collaborate with data scientists, analysts, and application teams to deliver reliable, high-quality datasets.

Participate in code reviews, solution design discussions, and architectural decision-making.

Required Skills & Qualifications:

12+ years of professional experience in Data Engineering, with at least 5+ years on AWS.

Strong hands-on expertise in AWS services: Glue, Redshift, S3, Lambda, EMR, Kinesis, Athena, DynamoDB, CloudWatch, and IAM.

Advanced proficiency in Python, PySpark, and SQL for building data transformations and pipelines.

Experience designing and managing data lakes and enterprise data warehouses on AWS.

Strong knowledge of ETL/ELT frameworks, CI/CD, DevOps practices, and infrastructure-as-code (Terraform / CloudFormation).

Experience with streaming technologies such as Kinesis, Kafka, or MSK.

Strong understanding of data modeling, performance tuning, and query optimization.