Sr. Data Engineer FULL TIME REMOTE

Lockheed Martin is partnering with PG&E, Salesforce, and Wells Fargo to deliver EMBERPOINT™, an initiative designed to transform wildfire prevention, detection, and response across the United States. The role involves designing and operating data pipelines for a scalable cloud-based data platform to support advanced sensing technologies and real-time analytics.

Responsibilities:

• Design, build, and operate the data pipelines that ingest, transform, catalog, and serve EMBERPOINT data platform and its AI/ML, Unified HMI, and command‑and‑control (C2) applications
• Work closely with the AWS Infrastructure Architect, AI/ML Engineers, Software Factory, MBSE team (Cameo→DOORS NEXT), and the Advisory Board to ensure data quality, security, and performance across the end‑to‑end mission workflow (Detection→Prediction→Response→Recovery)
• Integrate with streaming ingestion pipelines and data lake services to enable real-time analytics, operational applications, and predictive wildfire intelligence
• Work closely with data engineering, platform engineering, and application development teams to ensure the platform delivers high availability, strong performance, and secure data management

Requirements:

• 3 + years professional data-engineering experience
• SQL and Oracle experience
• ≥1 years designing and operating AWS-native data lakes for mission-critical or high-volume workloads
• B.S. Computer Science, Data Science, Information Systems, or related field (M.S. preferred)
• AWS knowledge
• Proven experience in SAFe/Agile environments, working with cross-functional teams (AI/ML, UX, Systems Engineering)
• Security Clearance: Secret
• Ability to work remotely: Full-time Remote Telework: The employee selected for this position will work remotely full time at a location other than a Lockheed Martin designated office/job site
• Deep knowledge of S3, Glue, Lake Formation, Kinesis, MSK, Redshift, Athena, QuickSight, Lambda, Step Functions, IAM, KMS
• Hands-on with AWS Glue, Spark, DBT, Airflow (or Managed Workflows for Apache Airflow)
• Proficient in Python (PySpark, Boto3), Scala, SQL, and Shell/Bash
• Experience integrating MBSE data from Cameo → DOORS NEXT into data-lake pipelines
• Knowledge of AI/ML data pipelines (SageMaker Feature Store, model-artifact versioning)
• Experience with data ingestion, Object Storage and data paths, ingest orchestration, ETL, relational and non-relational database with autonomousDB