Engineering & IT · New Orleans, LA

Data Engineer jobs in New Orleans, LA

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.

16
Open roles today
$35–$88/hr
Typical pay range
$121k
Median, full-time
5
Fresh in this list

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01

Open data engineer roles

12 shown of 16 · sorted by freshness

PROJECT - Data Engineer II

Deloitte · New Orleans, LA
$71.3k - $140.6k

Position Summary Our Deloitte AI & Engineering team works to transform technology platforms, drive innovation, and help make a significant... ...fuel growth through innovation. Work you'll do As a PROJECT - Data Engineer…

Posted 2d ago
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AI/Data Engineer

Zuven technologies Inc · New Orleans, LA

We are seeking an AI Data Integration Engineer with strong hands-on experience in Snowflake, healthcare claims data, and practical AI/LLM integration. This role will lead the creation of a sanitized claims data layer (Sn…

Posted 2d ago
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Cyber Security & Risk Strategy Consultant

Deloitte · New Orleans, LA
$82.6k - $162.8k

in Computer Science, Information Technology, Risk Management, Engineering, or a similar fieldProfessional certifications such as Certified... ...solutions, security information and event management platforms, or data los…

Posted 2d ago
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Cloud Security Engineer Manager

Deloitte · New Orleans, LA
$118.7k - $243.7k

sustainment of zero trust architectures to safeguard critical assets and data against emerging cyber threats.Serve as the subject matter... ...and Firewall Teams, Application Teams, Server Teams, Cloud Engineering Teams…

Posted 3d ago
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Analyst, Asbestos

Eurofins USA Environment Testing · New Orleans, LA · Full-time
$22 - $24 per hour

Assurance programs and SOP’s and must be knowledgeable of both job-specific routine and complex analyses. The analyst validates and reviews data for accuracy, and uploads laboratory data into the LIMS that ultimately gen…

Posted 1w ago
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AWS Data Engineer - II

Syms Strategic Group, LLC (SSG) · New Orleans, LA · Full-time
$85.39k - $116.98k

Syms Strategic Group (SSG) is seeking a talented Senior Systems Engineer (Amazon Web Services (AWS) Data Engineer) - II Location: Remote Department: Veterans Affairs (VA) Type: Full Time Min. Experience: Experienced Secu…

Posted 1w ago
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.NET ASP.NET Developer - REMOTE

NTT DATA, Inc. · New Orleans, LA
$68.08k - $118.19k

Req ID: 384836 NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization, apply now. We are…

Posted 3w ago
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IT Support Technician

St Thomas Community Health Center · New Orleans, LA · Full-time, Part-time

Job Summary: As an IT Support Technician, you will provide technical support for PCs, laptops, printers, network issues, software updates, and end-user support for all IT services. The ideal candidate should be able to t…

Posted 1mo ago
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Senior Solutions Engineer

Susco · New Orleans, LA · Full-time
$115k - $150k

$150,000 Remote Details: Fully Remote, Working Business Hours Central Time Role Summary Seeking highly independent senior engineers who can combine software development, business analysis, client consulting, and sales en…

Posted 2mo ago
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Support Services Technician I

BramTech Solutions Inc · New Orleans, LA

Support Services Technician I Company: BramTech Solutions, Inc. Location: New Orleans, LA About Us: BramTech Solutions is a leading IT services company based in New Orleans, Lousiana. We specialize in providing Managed I…

Posted 5mo ago
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02

What data engineers earn in New Orleans

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 New Orleans 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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