Pay
In line with similar jobs
$118K–$178K against $127K–$190K, the middle half of what similar US postings state.
From 2,133 postings in the last year. Stated ranges, not salaries paid.
Hanover, MD, United States
Live, first seen by us 23 days agoWe offer a comprehensive and competitive benefits package. Employee benefits vary by role, however, may include Health and Wellness, Mental Health, Retirement Savings, Life and Disability, Paid Maternity and Parental Leave, Paid Time Off, Tuition Reimbursement, and an Employee Assistance Program. Compensation $118,000.00 - $177,800.00Read the full posting
Employment type in the employer’s posting: Full timeFrom the employer’s posting
Must be a US citizen
Design, build, and maintain batch data pipelines and ingestion workflows
Implement ETL/ELT processes to extract, transform, validate, and load data
Implement validation routines, anomaly detection, and automated integrity checks
Support data modeling, schema design, DDS topic development, and database architecture
Build, maintain, and deploy data products and analytics solutions on cloud platforms
Design, build, and maintain batch data pipelines and ingestion workflows.
Implement ETL/ELT processes to extract, transform, validate, and load data from multiple sources.
Implement validation routines, anomaly detection, and automated integrity checks.
Support data modeling, schema design, DDS topic development, and database architecture.
Build, maintain, and deploy data products and analytics solutions on cloud platforms (e.g., Azure).
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.
Ability to obtain and maintain a DoW security clearance. Must be a U.S. citizen.
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.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
In line with similar jobs
$118K–$178K against $127K–$190K, the middle half of what similar US postings state.
From 2,133 postings in the last year. Stated ranges, not salaries paid.
Day 23
Similar jobs usually come down between day 6 and day 54.
At Oceaneering International, jobs usually come down by about day 31.
From 11,032 similar postings that came down, and 11 of Oceaneering International’s. Coming down is not always a hire.
7 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Experience with Linux and scripting languages. - Proficiency in Python, Java, C++, C#, or related languages. - Experience with Jira, Git, or similar tools.
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.
- 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.
- 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.
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. - Design, build, and maintain batch data pipelines and ingestion workflows.
- 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.
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New Data Engineer postings at the employers we follow are up 8% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
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.
Essential Qualifications
Preferred Qualifications
Additional
Additional duties as assigned.
We offer a comprehensive and competitive benefits package. Employee benefits vary by role, however, may include Health and Wellness, Mental Health, Retirement Savings, Life and Disability, Paid Maternity and Parental Leave, Paid Time Off, Tuition Reimbursement, and an Employee Assistance Program.
Compensation $118,000.00 - $177,800.00
Selected passages from the saved posting. Check the full description for conditions and exceptions.
We offer a comprehensive and competitive benefits package. Employee benefits vary by role, however, may include Health and Wellness, Mental Health, Retirement Savings, Life and Disability, Paid Maternity and Parental Leave, Paid Time Off, Tuition Reimbursement, and an Employee Assistance Program. Compensation $118,000.00 - $177,800.00
Hanover, MD, United States
Working pattern and location restrictions need checking in the full posting.
- Strong problem‑solving, communication, and organizational skills. - Ability to obtain and maintain a DoW security clearance. - Must be a U.S. citizen. Preferred Qualifications