Senior Data Engineer

Sr Data Engineer

Tenure: Min. 3 months (potential for extension)

Contract. Remote.

We are seeking a Sr. Data Engineer to join our technology team. This role is a hands-on position responsible for the build and continued evolution of the data platform, business applications and integration tools. We are looking for a hands on engineer that can recommend best practices to work with enterprise data. The ideal candidate is going to be a hands on engineer, and very strong with AWS Products to help build out data pipelines, create jobs, manage the quality of the data warehouse and integrated tools.

RESPONSIBILITIES

• Design, develop, and maintain scalable, efficient data pipelines to support ETL/ELT processes across multiple sources and systems
• Partner with Data Science, Analytics, and Business teams to understand data needs, prioritize use cases, and deliver reliable datasets and models
• Monitor, optimize, and troubleshoot data jobs, ensuring high availability and performance of data infrastructure
• Build and manage data models and schemas in Redshift and other data technologies, enabling self-service analytics
• Implement data quality checks, validation rules, and alerting mechanisms to ensure trust in data
• Leverage AWS services like Glue, Lambda, S3, Athena, and EMR to build modular, reusable data solutions
• Drive improvements in data lineage, cataloging, and documentation to ensure transparency and reusability of data assets
• Create and maintain technical documentation and version-controlled workflows (e.g., Git, dbt)
• Contribute to and promote a culture of continuous improvement, mentoring peers and advocating for scalable and modern data practices
• Participate in sprint planning, code reviews, and team retrospectives as part of an Agile development process
• Stay current on industry trends and emerging technologies to identify opportunities for innovation and automation
• Advanced Python, including experience building APIs, scripting ETL processes, and automating workflows
• Expert in SQL, with ability to write complex queries, optimize performance, and work across large datasets
• Hands-on experience with AWS data ecosystem including Redshift, S3, Glue, Athena, EMR, EC2, DynamoDB, Lambda, and Redis
• Strong understanding of data warehousing and data modeling principles (e.g., star/snowflake schema, dimensional modeling)
• Familiarity with dbt Labs and modern ELT/analytics engineering practices
• Experience working with structured, semi-structured, and unstructured data