Title: Senior Data Engineer
Location: Rockville, Maryland
Target Start Date: June 1, 2025
Type: contract
Pay Rate: DOE
The Data Engineer will design, build, and maintain scalable, cloud-native data infrastructure on AWS to support analytics initiatives. The ideal candidate will have strong experience with AWS data services, pipeline development, and modern data engineering best practices. Experience with Generative AI is a plus and highly valued.
The Senior Data Engineer will:
Design, implement, and maintain scalable ETL/ELT pipelines using AWS-native tools (Glue, Lambda, Step Functions).
Build and manage data lakes and data warehouses (S3, Redshift, Athena) for structured and semi-structured data.
Develop and optimize batch and streaming data pipelines using tools like Apache Spark, Kafka, Kinesis, or Flink.
Implement data cataloging, lineage, and governance using tools like Glue Catalog and Lake Formation.
Ensure data quality, integrity, and reliability through validation, alerting, and monitoring (CloudWatch, SNS).
Create and maintain curated data models and data marts to support reporting and machine learning.
Enable self-service analytics by integrating with BI tools such as QuickSight.
Optimize for cost, performance, and scalability across data pipelines and infrastructure.
Collaborate with ML engineers, analysts, and product teams to deliver data-driven solutions.
Ensure security best practices with least-privilege IAM configurations.
Build modular, reusable pipeline components for scalability and maintainability.
Leverage infrastructure-as-code tools (e.g., Terraform or CloudFormation) for consistent deployments.
Utilize orchestration tools like Apache Airflow and AWS Step Functions.
Deliver systems with high availability (99.9% uptime) and proactive monitoring.
Maintain thorough documentation and onboarding materials for engineering continuity.
7+ years of experience in data engineering or related fields.
3+ years building data platforms on AWS (S3, Glue, Redshift, EMR, Lambda, etc.).
Proven track record in leading technical projects and mentoring junior engineers.
Experience in Agile/Scrum development environments.
Experience migrating legacy systems to modern cloud platforms is a plus.
AWS Certified Data Analytics – Specialty (optional)
Experience using dbt for data transformation
Familiarity with data mesh or lakehouse architectures
Experience with ML pipelines (feature stores, model input pipelines)
Proficiency with Linux systems
Background in production support and operations
Strong problem-solving and debugging abilities
Excellent communication and collaboration skills
Ownership mindset and ability to lead cross-functional initiatives
Experience mentoring and coaching engineers
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