Engineering & IT · Baltimore, MD

Data Engineer jobs in Baltimore, MD

Data engineers build the pipelines and warehouses that move data from source systems to the people and models that need it, keeping it fresh, correct, and queryable at scale.

201
Open roles today
$39–$99/hr
Typical pay range
$135k
Median, full-time
8
Fresh in this list

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01

Open data engineer roles

12 shown of 201 · sorted by freshness

Security Data Engineer

Shield Consulting Solutions · Linthicum, MD · Full-time
$160k - $170k

None Basic Requirements: ~7 years of experience as a software engineer ~ Bachelor’s degree in a technical discipline ~4 additional... ...approvals, continuous monitoring and assessment, and network data gathering across…

Posted today
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Jr. Database Engineer

Shield Consulting Solutions · Linthicum, MD · Full-time
$125k - $135k

: ~5 years of applicable professional experience in database engineering ~ Bachelor’s degree in Computer Science or related discipline... ...and approvals, continuous monitoring and assessment, and network data gathering…

Posted today
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Sr. Data Analytics Engineer

Under Armour · Baltimore, MD · Full-time
$125k - $165k

apply to this position on the Internal Career Site Here. Purpose of Role Under Armour is seeking a highly motivated Sr. Data Analytics Engineer to join our Enterprise Data Management & Analytics team. This role plays a k…

Posted 3d ago
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Reverse Engineer / Malware Analyst - FUTURE NEED

Cipher Tech Solutions · Linthicum Heights, MD
$43.27 - $79.33 per hour

Have you ever played with Ghidra and/or IDA Pro disassemblers? Can you fluently read x86 / x64 assembly? Cipher Tech seeks Reverse Engineers/ Malware Analysts, who also love the traditional side of software development!…

Posted 4d ago
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Information Security Engineer- Data Security

Hunt Valley, MD · Full-time
$85k - $112.5k

Job Description The Information Security Engineer will be a part of the enterprise Data Security and Governance, Risk, & Compliance program with focus on developing and scaling data security controls, insider risk manage…

Posted 5d ago
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Data Engineer

Baltimore, MD
$89.6k - $198.4k

Data Engineer Position Description CGI Federal is seeking a Data Engineer to support a federal agency in modernizing its fraud control strategy. This senior technical role is part of a high impact team responsible for re…

Posted 1w ago
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Software Engineer (Data Management)

Themis Insight · Linthicum Heights, MD · Full-time

defined problem space. We bring Public and Private, Civilian and Military expertise to every case. We are hiring a Software Engineer (Data Management) in Linthicum Heights, MD. Position location is subject to change base…

Posted 1w ago
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Database Engineer 2

Lentech Inc. · Linthicum, MD · Full-time
$107k - $115k

Lentech is hiring a Mid Database Engineer As part of the Secure the Enterprise initiative, develop capabilities to shift from the current... ...approvals, continuous monitoring and assessment, and network data gathering…

Posted 1mo ago
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Database Engineer 3

Lentech Inc. · Linthicum, MD · Full-time
$192k - $220k

automation, streamlined processes and approvals, continuous monitoring and assessment, and network data gathering across the entire life cycle of a project. The Database Engineer will direct the development of complex sy…

Posted 1mo ago
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Cybersecurity Data Engineer

Shield Consulting Solutions · Linthicum, MD · Full-time
$220k - $230k

discipline (e.g., statistics, mathematics, operations research, engineering or computer science). ~10 years of experience analyzing... ...developing analytics ~10 years of experience programming with data analysis softwa…

Posted 1mo ago
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02

What data engineers earn in Baltimore

Hourly first — that's how the offer arrives

ExperienceHourlyAnnual, full-time
Entry level $39–$54 $82k–$113k
Mid level $54–$76 $113k–$158k
Senior $73–$99 $152k–$205k

Adjusted for the Baltimore market from national ranges.

03

What employers ask for

The skills these listings keep naming

SQL and data modelingPython or ScalaAirflow or similar orchestrationSpark or other batch processingWarehouses (Snowflake, BigQuery)dbtStreaming (Kafka)Data quality testingCloud infrastructure
04

Interview questions worth rehearsing

With the thing the interviewer is actually listening for

Design a pipeline that loads data from a production database into a warehouse daily.

Cover extraction strategy, incremental loads versus full refresh, idempotency, and monitoring. Saying how you would backfill after a failure shows real pipeline experience.

How do you handle late-arriving or duplicate data?

Discuss idempotent upserts, watermarks, and dedup keys. This is a daily reality of the job, so a concrete example lands well.

Batch or streaming — how do you decide?

Anchor on the actual freshness requirement and cost. Most 'real-time' asks are fine at minutes; recognizing that is the mature answer.

A stakeholder says the numbers in their dashboard are wrong. Walk me through your debugging.

Trace lineage from the dashboard back to the source, isolating which layer diverged. Showing calm, structured lineage-tracing is the point of the question.

How do you model data for analytics — star schema, wide tables, something else?

Show you know the classic patterns and modern warehouse economics, and that you choose based on query patterns and team skill, not doctrine.

How do you test data pipelines?

Talk about schema and freshness checks, row-count and distribution tests, and tools like dbt tests or Great Expectations — plus alerting when they fail.

Tell me about a pipeline that failed badly and what you changed.

Structure it like an incident review: impact, cause, fix, prevention. Emphasize the durable improvement, such as monitoring or contract enforcement.

05

Resume tips that move the needle

For data engineers specifically — generic advice costs you here

01

State data scale plainly — rows per day, terabytes managed, pipeline counts — because it is the first thing hiring managers scan for.

02

Name your orchestration, processing, and warehouse tools per role; the modern stack (Airflow, dbt, Snowflake) is a keyword screen.

03

Highlight reliability outcomes: pipeline failure rates, data freshness SLAs met, incident reductions.

04

Show cost work if you have it — warehouse spend is a live concern and optimization stories differentiate.

05

Mention who consumed your data (analysts, ML teams, executives) to show you build for users, not just movement.

06

Where this role goes

Typical progression

01 Junior Data Engineer
02 Data Engineer
03 Senior Data Engineer
04 Staff Data Engineer
05 Data Platform Lead
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