Engineering & IT · Jacksonville, FL

Data Engineer jobs in Jacksonville, FL

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.

112
Open roles today
$35–$88/hr
Typical pay range
$121k
Median, full-time
7
Fresh in this list

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01

Open data engineer roles

12 shown of 112 · sorted by freshness

AAI Data Engineer - Enterprise Platform

FIS · Jacksonville, FL

care was taken to include all competencies needed to successfully perform in this position. However, for Americans with Disabilities Act (ADA) purposes, the essential functions of the job may or may not have been describ…

Posted yesterday
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Bus Unit Application Support Analyst I

TD Bank · Jacksonville, FL

provide coaching to others* Participates as subject matter expert on strategic initiatives involving system support* Analyzes company data to identify and recommend initiatives that positively and materially impact the f…

Posted yesterday
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Data Engineer

AppleOne · Jacksonville, FL
$90 per hour

Job Summary We are seeking a senior-level Data Engineer for an opportunity supporting enterprise People Data, HR analytics, and modern data architecture initiatives. This role is ideal for a data professional who enjoys…

Posted 5d ago
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Data Engineer

Jacksonville, FL · Temporary

Kforce has a client in Jacksonville, FL that is seeking a Data Engineer. Summary: We are seeking a Data Engineer to design, develop, and maintain modern data solutions that support enterprise reporting, analytics, and op…

Posted 5d ago
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Data Migration Analyst

Nymbus, Inc. · Jacksonville, FL
$110k - $125k

align with the Eastern Time Zone; candidates located in the Eastern or Central time zones are preferred. POSITION SUMMARY: The Data Migration Analyst supports the complete lifecycle of data migration for banks and credit…

Posted 6d ago
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Remote SQL Developer (SSIS, T-SQL)

Software Guidance & Assistance · Jacksonville, FL · Full-time
$92k - $118k

and resolve issues effectively Strong capability to reverse engineer existing code and improve it for efficiency Experience with Oracle... ...the latest T-SQL features while working with large volumes of data Develop, pr…

Posted 6d ago
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Senior Data Governance Analyst

Jacksonville, FL · Temporary

Kforce has a client in Jacksonville, FL that is in need of a Data Governance Analyst that will play a key role in supporting the development... ..., or similar tools Familiarity with the Architecture, Engineering & Const…

Posted 1w ago
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Data Center Operations Advisor

System One · Jacksonville, FL

Job Description Job Description Job Title: Data Center Operations Advisor Location: Jacksonville, FL Type: Contract Work... ...scale data center facilities in a leadership position. Develop engineering and maintenance op…

Posted 3w ago
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Senior Data Cloud Engineer

Dun & Bradstreet · Jacksonville, FL · Full-time

Future with Dun & Bradstreet At Dun & Bradstreet, we believe data has the power to create a better tomorrow. As a global leader in... ...Explore opportunities at dnb.com/careers . Sr. Data Cloud Engineer( s)(multiple pos…

Posted 4mo ago
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SQL Data Engineer

ARC Group · Jacksonville, FL

Job Description Job Description SQL DATA ENGINEER HYBRID (JACKSONVILLE, FL) ARC Group has an immediate opportunity for a Senior SQL Data Engineer! This position is a hybrid position located in Jacksonville, FL, working 2…

Posted 4mo ago
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02

What data engineers earn in Jacksonville

Hourly first — that's how the offer arrives

ExperienceHourlyAnnual, full-time
Entry level $35–$49 $73k–$102k
Mid level $49–$68 $102k–$141k
Senior $65–$88 $136k–$183k

Adjusted for the Jacksonville 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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