Senior Data Engineer

Steer Bridge is a modern technology company delivering innovative, mission‑focused solutions to the U.S. Government and private sector. Leveraging deep expertise in federal acquisition, digital transformation, and emerging technologies, we deliver agile, commercial‑grade capabilities that accelerate operational effectiveness and drive measurable mission success.

At the core of Steer Bridge is our people—especially the veterans whose leadership, problem‑solving mindset, and commitment to excellence elevate every project we support. We don’t simply hire exceptional talent;
we cultivate it
, creating meaningful career pathways for veterans, military spouses, and professionals who share our passion for advancing technology and strengthening the missions we serve.

Steer Bridge seeks a highly skilled and motivated individual to join our team as a Senior Data Engineer to align data solutions to business requirements by planning and managing data infrastructure and strategy for our AI/ML Maintenance, Sustainment, and Deployment Planning Project. Our team is dedicated to harnessing the power of AI/ML to increase parts availability and reduce maintenance wait times, ultimately maximizing aircraft availability.

In this role, you will be responsible performing Data Engineering tasks within the existing systems of record with multiple databases. Your mission will be to enhance and optimize data entry, management and extraction within this database to ensure its usability within our proprietary system. Data management activities include performing data quality checks, analysis, presenting data and documenting the process. The ideal candidate is a quick learner, curious, innovative, results-oriented and has strong interpersonal skills

• Advanced data modeling (conceptual, logical, and physical) with emphasis on scalability and maintainability.
• Strong understanding of database paradigms (relational, No
  
  SQL, graph, time-series, and document-based).
• Expertise with modern data warehousing platforms (Redshift, Snowflake, Big Query).
• Deep understanding of dimensional modeling (star/snowflake schemas) and data vault techniques.
• Experience designing for both OLTP and OLAP workloads.
• Proficiency with schema evolution, metadata-driven pipelines, and data versioning strategies.
• Implementing data retention, archival, and lifecycle policies.
• Project
  
  Experience:
• Delivered optimized, production-grade data models supporting analytics, reporting, and ML workflows, aligning with established architecture and performance standards.
• Hands‑on experience with distributed processing tools (Apache Kafka, Airflow, Spark, Flink, NiFi).
• Skilled in building and orchestrating batch and real‑time pipelines on cloud platforms (AWS Glue, GCP Dataflow, Azure Data Factory).
• Deep understanding of incremental processing, idempotency, schema evolution, and backfill logic.
• Proficient in pipeline automation, observability, and monitoring (metrics, logging, alerting).
• Strong Python development for ETL — modular, testable, reusable, and performance‑optimized.
• Knowledge of workflow dependency management, retries, and failure recovery strategies.
• Project
  
  Experience:
• Owned the end‑to‑end design and implementation of fault‑tolerant, high-throughput pipelines integrating diverse data sources while maintaining data quality and SLAs.

• Deep expertise in AWS, GCP, or Azure data ecosystems.
• Experience building and managing cloud-native data solutions (Data Lakes, Data Warehouses, Data Mesh).
• Strong understanding of cloud storage (S3, Blob), managed databases (RDS, DynamoDB), and compute (EMR, Dataproc, ECS).
• Cost governance and performance optimization for large-scale data workloads.
• Knowl…