Software Engineer III, DB/Data Assurance

Oceaneering•Hanover, MD

12d•$118,000 - $177,800

About The Position

OTECH produces and maintains unique underwater systems, typically for US Navy and other US Government Department of War customers. Our projects are all one-of-a-kind, ranging from quick burn to lifecycle management of fielded systems. As a data engineer at Oceaneering Technologies (OTECH), you will be responsible for developing, maintaining, and optimizing data storage systems. The data engineer will support multiple stakeholders across the project, including software developers, systems engineers, integrated logistics support team members, and project managers. The ideal candidate should possess strong technical abilities to solve complex data problems, a willingness to learn new technologies/tools, and be comfortable articulating data concepts to stakeholders of varying levels of data proficiency. This role is responsible for ensuring that database systems and the data flowing through them are accurate, consistent, secure, traceable, and reliable throughout the application lifecycle. The role combines database development with data-quality and verification responsibilities. The assurance portion of the role requires strong knowledge of data verification, validation, provenance, and configuration control. The developer should be able to establish measurable data-quality criteria, implement automated integrity and regression tests, reconcile data between producers and consumers, and provide evidence that stored or transmitted data remains complete and correct. This includes supporting requirements traceability, test automation, logging/auditing, cybersecurity controls, backup and recovery, and root-cause analysis of data-related defects. In a distributed or mission-oriented system, the role may also involve validating data exchanged through messaging middleware, APIs, DDS/Kafka interfaces, containers, and other distributed services. The ideal candidate combines software-development discipline with a verification mindset—understanding not only how to store and transform data, but how to demonstrate that the resulting data can be trusted.

Requirements

BS in Computer Science, Computer/Electrical Engineering, Mathematics, Data Science, or related field (or commensurate experience).
5+ years of practical data engineering experience.
Advanced SQL proficiency and experience with relational database design.
Experience with data ingestion tools and building ETL/ELT pipelines.
Working knowledge of cloud solutions and workflow/pipeline orchestration tools.
Strong problem‑solving, communication, and organizational skills.
Ability to obtain and maintain a DoW security clearance.
Must be a U.S. citizen.

Nice To Haves

Experience with cloud data warehouses and large‑scale data systems.
Experience with Linux and scripting languages.
Proficiency in Python, Java, C++, C#, or related languages.
Experience with Jira, Git, or similar tools.
Experience with NoSQL systems (e.g., MongoDB, Cassandra, Neo4j).
Experience working with large datasets and distributed data environments.
Experience with MBSE/Digital Twin tools (Cameo, Syndeia, PLM/ERP).
Familiarity with DDS middleware and distributed messaging systems.
Knowledge of data verification, provenance, configuration control, and automated QA/QC.

Responsibilities

Design, build, and maintain batch data pipelines and ingestion workflows.
Develop, optimize, and maintain cloud‑enabled data infrastructure and storage solutions.
Implement ETL/ELT processes to extract, transform, validate, and load data from multiple sources.
Automate data workflows for ingestion, transformation, aggregation, and quality enforcement.
Build, maintain, and deploy data products and analytics solutions on cloud platforms (e.g., Azure).
Partner with cross‑functional teams to create dashboards and visualization tools.
Ensure data accuracy, consistency, traceability, and security across all systems and interfaces.
Implement validation routines, anomaly detection, and automated integrity checks.
Support data modeling, schema design, DDS topic development, and database architecture.
Monitor system performance and implement optimization strategies for reliability and efficiency.
Develop and maintain data compression and storage‑optimization strategies.
Contribute to data management CDRL materials and documentation.
Communicate effectively with technical and non‑technical team members.
Support verification, configuration control, auditing, and compliance requirements.
Provide feedback on software and data design choices and integration approaches.