Data Engineer Staff

Lockheed Martin is looking for a Data Engineer who will deliver end to end, full stack data solutions across the complete data processing pipeline. The role involves designing, building, and operating scalable pipelines for data analytics while ensuring security and compliance with standards.

Responsibilities:

• Build, test, and maintain robust data pipelines (batch & streaming) that clean, transform, and aggregate raw data into analytic ready data stores
• Implement data quality checks, smart caching, and virtualization techniques to guarantee consistency and reliability
• Build automated data management conduits that support machine learning data flows
• Collaborate with the Data Architect to create conceptual, logical, and physical data models that support business needs
• Define functional capabilities, security, backup, and recovery specifications for each solution
• Design and maintain systems that collect, store, and present data across the enterprise
• Conduct data profiling, requirement analysis, and performance tuning throughout the solution lifecycle
• Deploy, monitor, and optimize ETL/ELT processes (e.g., Informatica, Talend) and related reporting/analytics layers
• Develop and implement data mining and data warehousing programs to enrich the enterprise data ecosystem
• Identify and resolve production incidents; tune system parameters for optimal throughput and latency
• Evaluate, integrate, and validate new releases or platform upgrades
• Manage the compilation, cataloging, caching, distribution, and retrieval of data and maintain test data records
• Define and enforce best practice standards, certification processes, and metadata management policies for data objects
• Participate actively in the Data Governance Working Group
• Implement data management standards, requirements, and specifications and ensure compliance with data classification and handling rules through access control and security best practices
• Assist early stage risk identification and mitigation for task order activities
• Support Critical Design Reviews (CDRs) and advise Integrated Product Teams (IPTs) on data related risks and mitigation strategies
• Serve as the technical liaison to Systems Engineering, IPT engineers, and other disciplines to ensure complete, documented requirements allocation for IT and data systems
• Prepare and release engineering drawings and associated data system documentation
• Advise on and design the integration of new data technology solutions (e.g., IBM Cloud Pak for Data) into the SOFSA enterprise IT environment
• Advise higher level leadership on critical data management issues and emerging technology trends
• Report directly to the Data Architect and provide status updates on pipeline health, performance metrics, and risk registers
• Apply data acquisition, cleaning, transformation, and ingestion best practices for machine learning data conduits
• Assess and address methodological limitations to ensure reliable data delivery
• Read, interpret, write, modify, and execute simple scripts (e.g., PERL, VBS) on Windows and UNIX systems for parsing large files, automating manual tasks, and fetching/processing remote data
• Record, manage, and validate test data
• Establish data security controls, develop data dictionaries, and apply data mining techniques (e.g., file system searches)
• Perform data pre processing (imputation, dimensionality reduction, normalization, transformation, extraction, filtering, smoothing)
• Conduct transformation analytics (aggregation, enrichment, processing)

Requirements:

• Bachelor's degree in Artificial Intelligence, Computer Science, Information Systems, Data Engineering, or a related field (Master's preferred)
• Data-mining and data-warehousing principles
• Database management systems, query languages, table relationships, and views
• Proficiency with Hadoop, Java, Python, SQL, Hive, and PIG for data exploration
• DataOps processes and best practices
• Data-security roles and responsibilities; ability to implement access-control and encryption safeguards
• Knowledge of how to collect, store, monitor, and validate test data
• Ability to assess methodological limitations and recommend mitigation strategies
• IBM Cloud Pak for Data (CP4D) – Advanced
• Oracle / Microsoft SQL Server – Advanced (schema design, performance tuning)
• Microsoft Power BI Report Server – Proficient
• Deltek COBRA – Working knowledge
• Microsoft SharePoint – Working knowledge
• SAP – Working knowledge
• Teamcenter – Working knowledge
• Scripting – Python, PowerShell – Basic to intermediate (data extraction, automation)
• Data modeling & metadata management tools – Advanced
• ETL/ELT design (Informatica, Talend) – Preferred
• Cloud & distributed data platforms (AWS, Azure, GCP) – Preferred
• Experience with creation of Analytical Databases – Preferred
• Additional scripting – PERL, VBS (Windows/UNIX) – Basic
• Hadoop, Java, Hive, PIG (for data exploration) – Familiarity
• Relevant certifications (e.g., IBM Certified Data Engineer, TOGAF, Certified Data Management Professional, Security+) are a plus