Engineering & IT · San Antonio, TX

Data Engineer jobs in San Antonio, TX

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.

106
Open roles today
$35–$87/hr
Typical pay range
$120k
Median, full-time
9
Fresh in this list

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01

Open data engineer roles

12 shown of 106 · sorted by freshness

Substation Technical Specialist

HDR · San Antonio, TX

electricity is generated, transmitted and delivered as global energy demands grow. From massive data centers to modernizing transmission systems, our industry-recognized engineers and scientists have been at the forefron…

Posted 2d ago
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Senior AI Data Scientist Developer

USAA · San Antonio, TX · Full-time
$143.32k - $273.93k

degree in mathematics, computer science, statistics, science, engineering, or another quantitative discipline, or 4 years of relevant education... ...We expect 6+ years of experience in predictive analytics or data analy…

Posted 2d ago
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Data Platform Engineer

Syms Strategic Group, LLC (SSG) · San Antonio, TX · Full-time
$85.39k - $116.98k

Syms Strategic Group (SSG) is seeking a talented Data Platform Engineer Location: Remote Department: Veterans Affairs (VA) Type: Full Time Min. Experience: Experienced Security Clearance Level: Public Trust (MBI) Salary…

Posted 3d ago
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Senior Data Architect

Frost Bank · San Antonio, TX

design, deploy and administer applications? If so, the Senior Data Architect position could be your calling.At Frost, it’s about more... ...dataCommunicate new system strategies, designs, and methods to engineers through…

Posted 3d ago
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Information Security Engineer - Cybersecurity Focus

Kforce Technology Staffing · San Antonio, TX · Full-time
$123k - $163k

experience in information security, cybersecurity, or security engineering roles ~ In-depth knowledge of security principles across network... ...measures to safeguard enterprise systems, applications, and data Monitor a…

Posted 6d ago
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Senior Software and Data Engineer

KBR · San Antonio, TX · Full-time

Title: Senior Software and Data Engineer Belong. Connect. Grow. with KBR! KBR's National Security Solutions team provides high-end engineering and advanced technology solutions to our customers in the intelligence and na…

Posted 2w ago
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02

What data engineers earn in San Antonio

Hourly first — that's how the offer arrives

ExperienceHourlyAnnual, full-time
Entry level $35–$48 $73k–$100k
Mid level $48–$67 $100k–$140k
Senior $65–$87 $135k–$181k

Adjusted for the San Antonio 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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