Sr. Data Architect

Steer Bridge Strategies 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.

We are seeking a Senior Data Architect to lead the design and evolution of enterprise‑level data ecosystems. You will be responsible for architecting scalable, secure, and high‑performance data infrastructures that support mission‑critical aviation sustainment. This is a “player‑coach” role that requires high‑level strategic planning alongside hands‑on engineering execution.

• Health insurance
• Dental insurance
• Vision insurance
• Life Insurance
• 401(k) Retirement Plan with matching
• Paid Time Off
• Paid Federal Holidays

Architecture & Design: Design conceptual, logical, and physical data models for complex federal environments. Lead the transition from legacy on‑premises systems to modern, cloud‑native (AWS/GCP) data platforms.

Pipeline Development: Architect and oversee the build of automated ETL/ELT pipelines using Python, SQL, and PySpark to ingest and transform unstructured and structured data.

Cloud Data Warehousing: Implement and optimize enterprise data warehouses using tools like AWS Redshift
, Google Big Query
, AWS Glue
, and Databricks
.

Governance & Compliance: Establish data governance frameworks, metadata management, and data lineage in alignment with federal standards (HIPAA, FHIR, NIST).

Performance Optimization: Conduct index/partition design, query tuning, and sharding strategies to ensure high availability and scalability for real‑time analytics.

AI/ML Support: Design data architectures that facilitate AI/ML initiatives, including model training pipelines and real‑time inference in production environments.

Leadership: Mentor a team of data engineers, enforce software engineering best practices (CI/CD, unit testing, documentation), and serve as a technical bridge between stakeholders and delivery teams.

• Must be a U.S. Citizen.
• Masters’s Degree or Above in Systems Engineering, Computer Science or related field.
• An active security clearance or the ability to obtain one is required.
• Minimum 6+ years of experience to include:
  • Experience in data management, utilizing advanced analytics tools and platforms and Python.
  • Experience with Data Warehousing consulting/engineering or related technologies (Redshift, Databricks, Big Query, OADW, Apache Hive, Apache Lucene).
  • Experience in scripting, tooling, and automating large‑scale computing environments.
  • Extensive experience with major tools such as Python, Pandas, PySpark, Num Py, Sci Py, SQL, and Git;
    Minor experience with Tensor Flow, PyTorch, and Scikit‑learn.
  • Compliance: Deep understanding of data security and federal compliance requirements.

• Data Architecture and Design
  • Skills:
    • Data modeling (conceptual, logical, and physical)
    • Database schema design
    • Understanding of different database paradigms (relational, No
      
      SQL, graph databases, etc.)
    • ETL (Extract, Transform, Load) processes and tools
    • Experience with modern data warehousing solutions (e.g., Redshift, Snowflake, Big Query)
    • Understanding of dimensional modeling (star/snowflake schemas) and data vault techniques.
    • Experience designing for both OLTP and OLAP workloads.
    • Familiarity with metadata-driven design and schema evolution in data systems.
    • Experience defining data SLAs and lifecycle management policies.
    • Project
      
      Experience:
      
      Designing and implementing scalable data architectures that support business intelligence, analytics, and machine learning workflows.
• Data Pipeline…