Sr. Data Architect

3 days ago

Vienna, Virginia, United States SteerBridge Full time
SteerBridge Strategies is a CVE-Verified Service-Disabled, Veteran-Owned Small Business (SDVOSB) delivering a broad spectrum of professional services to the U.S. Government and private sector. Backed by decades of hands-on experience in federal acquisition and procurement, we provide agile, best-in-class commercial solutions that drive mission success.
Our strength lies in our people—especially the veterans whose leadership, discipline, and dedication shape everything we do. At SteerBridge, we don't just hire talent—we empower it, creating meaningful career paths for those who have served and those who share our commitment to excellence.
We are seeking a highly skilled Sr. Data Architect to support operations and sustainment of the F-35 and C-130 aircraft. This role involves designing, implementing, and managing data systems that support aircraft maintenance, logistics, performance analysis, and mission readiness. The ideal candidate will have experience in aerospace data systems, strong analytical skills, and a deep understanding of data governance in a defense environment. Benefits
  • Health insurance
  • Dental insurance
  • Vision insurance
  • Life Insurance
  • 401(k) Retirement Plan with matching
  • Paid Time Off
  • Paid Federal Holidays
Required
  • 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 10+ 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, BigQuery, 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, NumPy,SciPy, SQL, and Git; Minor experience with TensorFlow, PyTorch, and Scikit-learn.
Data Architecture and Design
  • Data modeling (conceptual, logical, and physical)
  • Database schema design
  • Understanding of different database paradigms (relational, NoSQL, graph databases, etc.)
  • ETL (Extract, Transform, Load) processes and tools
  • Experience with modern data warehousing solutions (e.g., Redshift, Snowflake, BigQuery)
  • 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 Development
  • Proficiency in tools like Apache Kafka, Airflow, Spark, Flink, or NiFi
  • Experience with cloud-based data services (AWS Glue, Google Cloud Dataflow, Azure Data Factory)
  • Real-time and batch data processing
  • Automation and monitoring of data pipelines
  • Strong understanding of incremental processing, idempotency, and backfill strategies.
  • Knowledge of workflow dependency management, retries, and alerting.
  • Experience writing modular, testable, and reusable Python-based ETL code.
  • Project Experience: Leading the development of highly available, fault-tolerant, and scalable data pipelines, integrating multiple data sources, and ensuring data quality.
Cloud Platforms and Services
  • Expertise in cloud environments (AWS, GCP, Azure)
  • Understanding of cloud-based storage (S3, Blob Storage), databases (RDS, DynamoDB), and compute resources
  • Implementing cloud-native data solutions (Data Lake, Data Warehouse, Data Mesh)
  • Experience with cost monitoring and optimization for data workloads.
  • Familiarity with hybrid and multi-cloud architectures.
  • Understanding of serverless data patterns (e.g., Lambda + S3 + Athena, Cloud Functions + BigQuery).
Project Experience: Migrating legacy data infrastructure to the cloud or developing new data platforms using cloud services, with a focus on cost efficiency and scalability. Big Data Technologies
  • Experience with big data ecosystems (Hadoop, HDFS, Hive, Spark)
  • Distributed computing, parallel processing, and handling petabyte-scale data
  • Tools for querying large datasets (Presto, Athena)
  • Understanding of lakehouse frameworks (Delta Lake, Iceberg, Hudi).
  • Familiarity with data compaction, schema evolution, and ACID guarantees in distributed storage
Project Experience: Building and managing big data platforms to enable large-scale analytics, often incorporating structured and unstructured data. Database Administration and Optimization
  • Expertise in database technologies (SQL, NoSQL, GraphDBs)
  • Query optimization, indexing, and partitioning strategies
  • Backup, replication, and disaster recovery planning
  • Understanding of query execution plans, cost-based optimization, and caching strategies.
  • Experience performing index and partition design based on query patterns.
  • Familiarity with data versioning and temporal tables.
  • Experience profiling and optimizing application code interacting with databases
Project Experience: Performance tuning for complex queries, implementing database replication and sharding strategies to support high availability and scalability. Data Governance and Security
  • Data privacy, encryption, and compliance with regulations (GDPR, CCPA)
  • Implementing data governance frameworks (data lineage, cataloging, metadata management)
  • Role-based access control and user management for sensitive data
  • Experience with automated policy enforcement and data lineage visualization tools (e.g., DataHub, Collibra, Alation).
  • Knowledge of data quality frameworks integrated into CI/CD pipelines.
  • Familiarity with data contract testing between producer and consumer teams.
Project Experience: Developing and implementing data governance policies and security controls across the organization's data assets, ensuring compliance with industry standards. Programming and Scripting Languages
  • Proficiency in Python and SQL
  • Experience with version control (Git) and CI/CD for data engineering (Gitlab, Jenkins, CircleCI)
  • API design and integration (Postman)
  • Strong understanding of object-oriented programming (OOP) principles and design patterns in Python.
  • Familiarity with software engineering best practices (modularity, testing, documentation, linting).
  • Understanding of algorithmic complexity (Big O notation) and ability to optimize code for scale.
  • Experience with parallel and distributed computation frameworks (Spark, Dask, Ray).
  • Ability to profile and debug performance bottlenecks in data workflows.
  • Use of type hinting, logging frameworks, and automated testing frameworks (pytest, unittest)
AI/ML Pipeline Support and Analytics
  • Experience in supporting data scientists with feature engineering, data wrangling, and model deployment
  • Knowledge of ML orchestration tools (MLflow, Kubeflow)
  • Hands-on experience with analytics tools (e.g.,Tableau, PowerBI)
  • Familiarity with feature store design and model feature lineage tracking.
  • Understanding of data versioning and reproducibility for ML workflows.
  • Experience supporting real-time model inference pipelines.
Project Experience: Designing architectures that support AI/ML initiatives, enabling scalable data pipelines for training models, and supporting experimentation in the production environment. Leadership and Mentorship
  • Leading data engineering teams, cross-functional collaboration with data scientists, analysts, and business units
  • Project management (Agile, Scrum, Kanban) and stake holder communication
  • Experience with mentorship and growing junior data engineers
  • Experience establishing data architecture standards and best practices.
  • Ability to review and approve technical designs for consistency and scalability.
  • Proven success in mentoring engineers in code quality, modeling, and system design
Project Experience: Leading the technical direction for large-scale data initiatives, suchasenterprisedatalakeimplementationsorthecreationofaunifieddataplatform. $120,000 - $135,000 a year A salary commensurate with experience will be offered. SteerBridge Strategies is proud to be an Equal Opportunity Employer. We are committed to creating a diverse and inclusive workplace where all qualified applicants and employees are treated with respect and dignity—regardless of race, color, gender, age, religion, national origin, ancestry, disability, veteran status, genetic information, sexual orientation, or any other characteristic protected by law. We also provide reasonable accommodations for individuals with disabilities in accordance with applicable laws. If you require assistance during the application process, we encourage you to reach out so we can support your needs. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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