Software Engineer III, DB/Data Assurance

Oceaneering International, Inc.; Bentwoods (MD); On-site; USD 95,000 - 130,000; Full time

Job summary

Oceaneering Technologies (OTECH) seeks an experienced data engineer to design, implement, and optimize data storage and pipelines for complex, one-of-a-kind projects in defense and government contexts.

You will build and maintain relational schemas, ETL/ELT processes, and automated data-quality checks, ensuring data accuracy, traceability, and secure handling across systems with Python, SQL, and various databases.

Qualifications

• Experience designing and maintaining relational databases.
• Proficient with ETL/ELT processes and data integration.
• Ability to verify data integrity across system boundaries.
• Experience with defense or government data systems is a plus.

Responsibilities

• Design and maintain relational database schemas.
• Develop ETL/ELT pipelines and data interfaces.
• Implement automated data-quality checks and validation routines.
• Collaborate with software, systems, and project management teams.

Skills

SQL

Python

Java

C++

Data modeling

ETL/ELT

Data quality

Tools

PostgreSQL

MariaDB/MySQL

SQL Server

Oracle

DDS

Kafka

JSON

XML

Avro

Job description

We are seeking an experienced data engineer to join our team! 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. Projects range 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, project managers. The ideal candidate should process 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. Typical work includes designing and maintaining relational database schemas, stored procedures, queries, data interfaces, ETL/ELT processes, and validation routines; verifying data integrity across system boundaries; identifying anomalous, incomplete, duplicated, or inconsistent data; and developing automated checks that confirm data conforms to defined schemas, business rules, interface specifications, and quality requirements. The developer should be proficient with DDS, SQL, and database technologies such as PostgreSQL, MariaDB/MySQL, SQL Server, or Oracle, along with scripting or development languages such as Python, Java, or C++. Experience with data modeling, schema/version management, transaction processing, indexing, query optimization, and structured data formats such as JSON, XML, or Avro is also valuable.
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.