Lead Data Engineer, SQL and Python

Requirements

• Bachelors degree in Computer Science, Data Engineering, Information Systems, or a related STEM discipline.
• Over 5 years of professional experience in data engineering, data pipeline creation, AI strategy, developer relations, or technical program management.
• Strong expertise in Python and SQL for data manipulation, transformation, and pipeline automation.
• Practical experience with data pipeline/orchestration tools (e.g., Flyte, Air Byte, Apache Airflow, Prefect, Luigi, or similar).
• Proficient with relational databases (Postgre
  
  SQL, MySQL, or equivalent).
• Robust technical understanding of generative AI, developer tools, and contemporary software development practices.
• Outstanding communication and storytelling capabilities, capable of engaging both technical and executive audiences.
• Familiarity with data pipelines in regulated sectors such as defense or aerospace is a plus.
• Knowledge of AI/ML data preparation, feature engineering, and training data management is preferred.
• Experience with streaming data platforms (e.g., Kafka, Spark Streaming, or similar).
• Knowledge of data visualization tools (e.g., Tableau, Power BI, or Grafana) for dashboard integration.
• Advanced credentials in AI ethics, MLOps, or enterprise architecture are desirable.
• Direct experience with AI‑assisted development tools (e.g., Git Hub Copilot, ChatGPT, internal LLMs).
• Proven success in building and sustaining technical communities.
• Exposure to containerization technologies (e.g., Docker, Kubernetes) and CI/CD for data pipeline deployment.
• Familiarity with API development (e.g., REST, Graph
  
  QL) for data service layers.
• Experience with Lockheed Martin's internal platforms such as Navigator and Genesis is advantageous.

• Design and implement comprehensive data pipelines to extract, transform, and deliver data from various sources to support AI adoption initiatives and analytics.
• Create ETL/ELT workflows using technologies such as Python, SQL, Flyte, and related orchestration tools to manage both structured and unstructured data effectively.
• Develop and maintain data models that are optimized for AI/ML training datasets, and adoption metrics, alongside executive dashboards.
• Establish automated checks for data quality, validation protocols, and continuous monitoring to ensure the reliability of pipelines and integrity of data.
• Build data infrastructure that tracks AI adoption KPIs, including training completion rates and tool usage metrics, for over 120,000 employees.
• Aggregate and harmonize data from internal platforms like LM Navigator and Genesis to facilitate consolidated adoption reporting.
• Compile adoption metrics, developer feedback, and industry trends into reports and decision packages for executive presentations.
• Generate both real‑time and batch data feeds for leadership dashboards that monitor AI maturity across various business functions.
• Integrate data from different internal systems, including HR and learning management platforms, into cohesive datasets geared for AI applications.
• Document data lineage, maintain data dictionaries, and uphold governance standards for all pipeline outputs.
• Advocate for AI ethics, security, and integrity across data workflows and within the wider developer ecosystem.
• Collaborate with IT and cybersecurity teams to guarantee secure data transfer and storage in both on‑premises and classified settings.
• Foster a dynamic AI developer community through hosting events, hackathons, and discussions geared towards data‑centric AI adoption.
• Act as a liaison between developers, data teams, product management, and leadership to align priorities and development strategies.
• Contribute to the AI Factory ecosystem by creating reusable data components, integration methodologies, and shared services.
• Partner with engineering leadership to identify gaps in tools and solutions, influencing product development based on feedback from developers and adoption analytics.
• Provide guidance and mentorship to junior team members on exemplary data engineering practices.

At Lockheed Martin, we are dedicated to pushing the boundaries of innovation and safety, addressing the worlds toughest challenges. We are seeking a highly motivated AI Adoption Data Specialist to join our vibrant team within the Artificial Intelligence Center (LAIC). This role is critical in driving the enterprise‑wide adoption of AI tools by designing robust data systems and leading initiatives that create measurable impacts.

We offer flexible work schedules, competitive compensation, and comprehensive benefits, including medical, dental, and life insurance, a 401(k) match, paid time off, and more. We prioritize our employees growth and well-being, striving to foster an inclusive culture bolstered by integrity and responsibility. If our mission resonates with you, we invite you to apply.