Why this role stands out
This hybrid role offers a fantastic opportunity to drive impactful data solutions for a federal contracting client, leveraging your Python and ETL expertise to build scalable data models and APIs. You'll thrive here if you're a self-motivated engineer with strong analytical skills and a desire for continuous learning within a dynamic Agile environment. Apply now to contribute to critical product launches and platform enhancements!
Quick overview
Job description
On behalf of our Federal Contracting client, ClearanceJobs Workforce Solutions is seeking a Senior Data Engineer (Python/ETL) to be a key contributor to both user-facing product launches as well as platform enhancements and stability. This role sits at the intersection of backend development and data engineering, owning the pipelines, data models, and APIs that move data from source systems to the product.
An active Top Secret security clearance is required. Work is primarily performed remotely, however regular client meetings in the Washington D.C. area are to be expected.
Responsibilities
- Develop core product features in ETL (Extract, Transform, Load) and GraphQL to support data processing and retrieval.
- Design and implement backend APIs in GraphQL to facilitate data interactions between different components of the product.
- Build and maintain ETL/ELT pipelines for efficient data processing and analytics, including ingestion from diverse structured and unstructured sources.
- Design scalable data models and schemas that support both transactional and analytical workloads.
- Orchestrate and schedule data workflows using tools such as Apache Airflow, Dagster, or Prefect.
- Implement data quality checks, validation, and monitoring to ensure accuracy, completeness, and reliability of data across the platform.
- Optimize query performance and pipeline efficiency for large-scale datasets.
- Collaborate with front-end team members to present data in a clear and user-friendly format, enhancing the product's user experience.
Qualifications
- Ability to own and manage concurrent initiatives, demonstrating effective judgment in prioritization and time management.
- Driven, self-managed, capable of conceiving and implementing solutions on your own and with a team.
- A strong desire to continuously improve and learn new technologies in a fast-paced Agile development environment.
- Excellent analytical and problem-solving skills, effective communication, attention to detail and high-quality work.
- Strong technical documentation ability to support the development process, including data flow and pipeline documentation.
- Effective communication and collaboration with designers, developers, and product managers.
- Ability and interest in mentoring junior and mid-level engineers to foster their growth and development.
- Bachelor's Degree in Computer Science, Computer Engineering or related field.
- 7+ yrs professional software engineering experience using Python, including at least 3 years focused on data engineering or ETL pipeline development.
- Experience building applications on cloud computing platforms such as AWS, Azure, GCP, using container technologies such as Docker and Kubernetes.
- Expert proficiency in SQL, including query optimization and performance tuning.
- Hands-on experience designing and building production data pipelines using Python data libraries (e.g., pandas, PySpark).
- Strong understanding of data modeling concepts, including relational and dimensional modeling.
Preferred Education/Experience
- Experience with various database architectures including relational (PostgreSQL) and graph (Neo4j).
- Experience building GraphQL backends.
- Experience with workflow orchestration tools such as Apache Airflow, Dagster, or Prefect.
- Experience with distributed data processing frameworks such as Apache Spark.
- Experience with streaming or event-driven data technologies such as Kafka, Kinesis, or change data capture (CDC).
- Experience with cloud data warehouses and lakes such as Snowflake, Redshift, Databricks, or S3-based lakes using Parquet/Delta formats.
- Experience with dbt or similar transformation frameworks, and data quality tooling such as Great Expectations.
- Experience managing and maintaining production infrastructure.
- Experience building platform capabilities for internal teams.
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