Engineering & IT · Indianapolis, IN

Data Engineer jobs in Indianapolis, IN

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.

101
Open roles today
$35–$87/hr
Typical pay range
$120k
Median, full-time
12
Fresh in this list

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01

Open data engineer roles

12 shown of 101 · sorted by freshness

AWS/Databricks Cloud Data Engineer

Moser Consulting · Indianapolis, IN · Full-time
$85k - $125k

respects the remarkable individuality of everyone's culture, history, and service. Description We are seeking a Senior Cloud Data Engineer to join our consulting team. In this role, you will design, build, and maintain s…

Posted yesterday
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SOX Auditor/Analyst

Robert Half · Indianapolis, IN

We are looking for an experienced Global SOX Auditor/Analyst to support a Contract engagement in Indiana. This role focuses on evaluating internal controls, executing SOX compliance activities, and partnering with stakeh…

Posted 2d ago
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Sr Principal Data, Analytics & AI Engineer

Eli Lilly and Company · Indianapolis, IN
$133.5k - $224.4k

best to work that truly matters for patients, we invite you to join us. We are seeking an experienced Senior Principal Data, Analytics & AI Engineer to join the Global DIA team within MQ Tech at Lilly. This role sits at…

Posted 3d ago
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Senior Data Scientist - Clinical Informaticist

Wolters Kluwer · Indianapolis, IN
$85.6k - $149.4k

Informaticist combines clinical expertise, healthcare informatics, and data science to support the development, implementation, and... ...Sentri7 Drug Diversion platform. Working closely with product, engineering, data s…

Posted 3d ago
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Data Analyst/FM Product Consultant

Guidehouse · Indianapolis, IN

Job Family: Data Management (DTA)Travel Required:Up to 10%Clearance Required:Ability to Obtain SecretWhat You Will Do:Guidehouse is currently seeking qualified Data Analysts & Product Managers to support Guidehouse's Def…

Posted 3d ago
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Rovo & AI Prompt Engineer

Accenture · Carmel, IN

processes that run it. That work changes the operating model an engineering organization runs on, the ways of working underneath it, and... ...We combine our strength in technology and leadership in cloud, data and AI wi…

Posted 3d ago
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Epic Radiant Analyst

TEKsystems · Indianapolis, IN
$75 - $90 per hour

Epic Radiant Analyst (Remote)Position OverviewWe are seeking an experienced Epic Radiant Analyst to join our team in a 100% remote capacity. This individual will play a key role in supporting, building, optimizing, and m…

Posted 3d ago
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Senior Server-Side Engineer

Bright Vision Technologies · Carmel, IN · Full-time
$100k - $150k

consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States. This is a... ...tremendous career growth potential. Job Title: Senior Server-Side Engineer Locati…

Posted 3d ago
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Cloud Security Engineer Manager

Deloitte · Indianapolis, IN
$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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SAP Data Migration Manager/Architect

Accenture · Carmel, IN

to create value and shared success for our clients, people, shareholders, partners and communities. Visit us at Are:A seasoned SAP data migration leader who thinks in blueprints and delivers at scale. You have the archit…

Posted 5d ago
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02

What data engineers earn in Indianapolis

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 Indianapolis 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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