We are seeking a Data Engineer with strong Databricks expertise to modernize and scale our Business Intelligence (BI) capabilities. This role will design and build data pipelines, deploy machine learning solutions, and o…
Engineering & IT · Tampa, FL
Data Engineer jobs in Tampa, 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.
225
Open roles today
$37–$93/hr
Typical pay range
$128k
Median, full-time
7
Fresh in this list
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01
Open data engineer roles
12 shown of 225 · sorted by freshness
$92k - $130k
JOB DESCRIPTION SUMMARY Greystar's D²AI organization ( Data, Digital, and AI) is responsible for the platforms, processes,... ...tools in your day-to-day work, and partnering effectively with engineering, analytics, and…
Symetra is seeking an Analytics Engineer to model data and provide clean datasets across the organization. You will build data marts and optimize ETL pipelines to enable analytics by data scientists, analysts, and engine…
Symetra is seeking an Analytics Engineer to help build the data platform powering our AI products. You will design and maintain pipelines and datasets, ensuring clean, reliable data for AI workflows and unstructured sour…
assigned as required Indepth understanding of HDFS architecture data storage and fault tolerance mechanisms Experience with HDFS... ...and solutions leveraging strengths from strategy and design to engineering, all fuele…
Job Description Job Description Graham Technologies is seeking a highly skilled Data Engineer to design, develop, and maintain enterprise data engineering solutions that support advanced analytics and modernize large-sca…
Black Cape Title: Python Data Engineer (Entry - Mid Level) Location: Tampa, FL Onsite: Expected to go onsite (into a SCIF) up to 5 days per week Clearance: TS/SCI (no poly required) ***If you do NOT have a US Citizenship…
Job Description Job Description Bridgeway is seeking a Data Engineer (BI) to design, develop, and maintain our data warehouse infrastructure and the semantic models, dashboards, and reporting that sit on top of it. This…
Strong hands-on experience in Python for data engineering and application development. Extensive experience with AWS cloud services, including S3, EMR, Glue, Lambda, IAM, EC2, ECS/EKS, CloudWatch, and Redshift. Strong ex…
$88k - $110k
position is at Philip Morris International The selection process will be fully managed by Philip Morris International. -- MDM Data Engineer- Tampa, Florida Be a part of a revolutionary change! At Philip Morris Internatio…
Job Description Job Description Job Title: Data Engineer – MEM SQL Location: New Jersey / Irving, TX / Tampa, FL Job Description: We are looking for an experienced Data Engineer with strong expertise in MEM SQL (SingleSt…
$80 - $85 per hour
Unlock your potential as a Data Engineer in a fully remote position, where you'll play a crucial role in advancing Big Data and Analytics initiatives. We are seeking a talented individual who is passionate about leveragi…
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What data engineers earn in Tampa
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $37–$51 | $77k–$107k |
| Mid level | $51–$71 | $107k–$148k |
| Senior | $69–$93 | $144k–$193k |
Adjusted for the Tampa market from national ranges.
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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.
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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.
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Mention who consumed your data (analysts, ML teams, executives) to show you build for users, not just movement.
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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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