The Lead Data Engineer / Data Architect will spearhead the creation of our next-generation "Analytics Core" within a closed, classified, on-premises environment. This mission-critical project will unify our 30-year legacy archive of diverse data-including reports, sensor data, imagery, and heavily geospatial intelligence-into a single, query-able, and AI-ready ecosystem.
Because our historical data is highly complex with deep attribution challenges, this is a "roll-up-your-sleeves" role. We expect a balance of approximately 60% hands-on data engineering (ETL pipeline construction, data cleaning, and mapping) and 40% data architecture (strategic design and governance).
As our management team upskills our dedicated in-house staff to execute the broader data migration, this role will act as the technical anchor. The Lead Data Engineer / Data Architect will build strong relationships, set clear technical standards, and seamlessly interface with transitioning staff to ensure the project's success.
Oceaneering is a global provider of engineered services and products, primarily to the offshore energy industry. We develop products and services for use throughout the lifecycle of an offshore oilfield, from drilling to decommissioning. We operate the world''s premier fleet of work class ROVs. Additionally, we are a leader in offshore oilfield maintenance services, umbilicals, subsea hardware, and tooling. We also use applied technology expertise to serve the defense, material handling, aerospace, science, and renewable energy industries.
Equal Opportunity Employer:
All qualified candidates will receive consideration for all positions without regard to race, color, age, religion, sex (including pregnancy), sexual orientation, gender identity, national origin, veteran status, disability, genetic information, or other non-merit factor.
REQUIRED
o Policy development
o Organizational goals for handling and using data
o Having led a data analysis team
o Ability to query a database
DESIRED
The salary range for this position is $118,600 - $177,800
ESSENTIAL
o Design the foundational multidimensional data models for complex, multi-modal data.
o Untangle 30 years of complex historical data to resolve attribution issues and establish a clean, authoritative data model.
o Act as the hands-on technical lead to build initial ETL/ELT pipelines using Python, SQL, and on-premises infrastructure.
o Develop programmatic solutions to clean, parse, and ingest legacy unstructured and structured data.
o Given that nearly all database records contain coordinate data, lead the integration between our on-premises ESRI portal and the new Analytics Core.
o Ensure spatial data seamlessly aligns with the multidimensional model.
o Establish standards for feature engineering, ensuring the database architecture is optimized for future Artificial Intelligence and Machine Learning applications within a classified environment.
o Enforce data governance, metadata tagging, and access control protocols in strict alignment with the DoD Data Strategy and classified network handling requirements.
o While management will handle direct personnel training, you must establish effective working relationships and technical interfaces with our evolving internal team:
§ Software Engineers: Interface with engineers transitioning into data engineering. Provide clear technical specifications, architectural blueprints, and constructive code reviews as they take over building scalable ETL/ELT pipelines.
§ GIS Specialist: Collaborate closely to integrate their programmatic GIS outputs into the broader AI-ready database. Bridge the gap between standard data engineering and specialized geospatial analytics.
§ Junior Data Manager: Partner to operationalize data governance. Define data rules and interface with them as they manage the Data Dictionary, enforce quality control, and properly tag legacy metadata.
§ General:
ADDITIONAL
ESSENTIAL
o Design the foundational multidimensional data models for complex, multi-modal data.
o Untangle 30 years of complex historical data to resolve attribution issues and establish a clean, authoritative data model.
o Act as the hands-on technical lead to build initial ETL/ELT pipelines using Python, SQL, and on-premises infrastructure.
o Develop programmatic solutions to clean, parse, and ingest legacy unstructured and structured data.
o Given that nearly all database records contain coordinate data, lead the integration between our on-premises ESRI portal and the new Analytics Core.
o Ensure spatial data seamlessly aligns with the multidimensional model.
o Establish standards for feature engineering, ensuring the database architecture is optimized for future Artificial Intelligence and Machine Learning applications within a classified environment.
o Enforce data governance, metadata tagging, and access control protocols in strict alignment with the DoD Data Strategy and classified network handling requirements.
o While management will handle direct personnel training, you must establish effective working relationships and technical interfaces with our evolving internal team:
§ Software Engineers: Interface with engineers transitioning into data engineering. Provide clear technical specifications, architectural blueprints, and constructive code reviews as they take over building scalable ETL/ELT pipelines.
§ GIS Specialist: Collaborate closely to integrate their programmatic GIS outputs into the broader AI-ready database. Bridge the gap between standard data engineering and specialized geospatial analytics.
§ Junior Data Manager: Partner to operationalize data governance. Define data rules and interface with them as they manage the Data Dictionary, enforce quality control, and properly tag legacy metadata.
§ General:
ADDITIONAL