Data Engineer Jobs in Indiana
Data Engineer jobs in Indiana are concentrated in Indianapolis, Fort Wayne, and Bloomington, where employers like Eli Lilly, Salesforce, and Indiana University anchor steady demand for pipeline development, cloud data architecture, and analytics engineering. Openings range from junior engineers supporting BI teams to senior architects designing enterprise data platforms for healthcare and life sciences clients. The Indianapolis tech corridor has made Indiana one of the more active Midwest markets for this role. See the openings below and apply to the ones that match your experience.
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Showing 5 of 39+ Data Engineer jobs
Location: Columbus, IN.
About the Role
We are hiring a Data Engineer with strong hands-on experience in building
high‑performance data pipelines for a heavy data analytics project. The candidate must be excellent at writing complex aggregations, understanding business processes and analytical requirements, and designing scalable data lake and data warehouse solutions. Experience across multiple data platforms (Databricks, Snowflake, Azure Data Factory, Synapse, etc.) is a strong advantage.
Key Responsibilities
1. Data Pipeline & ETL/ELT Development Develop, optimize, and productionize Spark (PySpark/Scala) pipelines.
Ingest, transform, cleanse, and aggregate large datasets from varied sources.
Implement scalable ETL/ELT logic for batch and near-real-time pipelines.
Apply best practices in partitioning, caching, Delta Lake optimization, and performance tuning.
2. Heavy Data Analytics & Business Understanding Write complex aggregation logic (window functions, rollups, grouping sets, analytical
functions).
Understand business KPIs, metrics, and analytical use cases.
Translate business needs into technical transformations and data models.
Validate data outputs against business logic and analytics expectations.
Collaborate with analysts on calculations: weekly/monthly aggregates, trend lines, performance metrics, dimensional rollups.
Ensure accuracy, consistency, and traceability of business-critical metrics.
3. Data Lake Engineering Build and maintain multi-layer Data Lake architectures (Bronze/Silver/Gold).
Work with Parquet, Delta Lake, ORC, and columnar storage formats.
Implement schema evolution, auditing, and metadata strategies.
4. Data Warehouse Engineering Design dimensional models: Star Schema and Snowflake Schema.
Build fact and dimension tables supporting analytics and reporting.
Optimize table structures, keys, and partitioning strategies.
5. Databricks (Added Advantage) Develop notebooks/jobs using PySpark/Scala.
Manage clusters, workflows, and Delta Live Tables.
Implement best practices for performance and cost efficiency.
6. SQL Engineering Strong command of SQL for aggregations, analytical functions, joins,profiling, andvalidation.
Write and optimize complex queries supporting dashboards, metrics, and reports.
7. Cloud Data Platforms Azure: Data Factory, Synapse Analytics, ADLS Gen2, Azure Functions (optional).
Snowflake: Virtual Warehouses, Snowpipe, Streams & Tasks, performance tuning.
8. Data Quality & Documentation Validate transformation logic against business rules.
Document data flows, transformation rules, aggregation logic, and data
dictionary/metadata.
Work with QA and analysts to ensure outputs match business expectations.
Required Qualifications
5+ years of hands-on data engineering experience.
Strong programming skills: Spark, Scala, Python.
Strong SQL skills (aggregations, analytical functions, large joins).
Experience with Data Lake and Data Warehouse concepts.
Experience with Spark-based processing (delta optimization, shuffle tuning, partitioning).
Experience with at least one cloud data ecosystem (Azure/AWS/GCP).
Preferred Skills
Experience with Databricks (highly desirable).
Experience with Snowflake or modern cloud DWH.
Experience with ADF/Synapse/Airflow/dbt for orchestration.
Knowledge of CI/CD for data pipelines.
Experience with large-scale data analytics environments.
Soft Skills
Strong understanding of business logic behind analytics outputs.
Ability to translate business metrics into technical transformations.
Strong problem-solving and debugging skills.
Good communication and cross-team collaboration.
Location: Columbus, IN.
About the Role
We are hiring a Data Engineer with strong hands-on experience in building
high‑performance data pipelines for a heavy data analytics project. The candidate must be excellent at writing complex aggregations, understanding business processes and analytical requirements, and designing scalable data lake and data warehouse solutions. Experience across multiple data platforms (Databricks, Snowflake, Azure Data Factory, Synapse, etc.) is a strong advantage.
Key Responsibilities
1. Data Pipeline & ETL/ELT Development Develop, optimize, and productionize Spark (PySpark/Scala) pipelines.
Ingest, transform, cleanse, and aggregate large datasets from varied sources.
Implement scalable ETL/ELT logic for batch and near-real-time pipelines.
Apply best practices in partitioning, caching, Delta Lake optimization, and performance tuning.
2. Heavy Data Analytics & Business Understanding Write complex aggregation logic (window functions, rollups, grouping sets, analytical
functions).
Understand business KPIs, metrics, and analytical use cases.
Translate business needs into technical transformations and data models.
Validate data outputs against business logic and analytics expectations.
Collaborate with analysts on calculations: weekly/monthly aggregates, trend lines, performance metrics, dimensional rollups.
Ensure accuracy, consistency, and traceability of business-critical metrics.
3. Data Lake Engineering Build and maintain multi-layer Data Lake architectures (Bronze/Silver/Gold).
Work with Parquet, Delta Lake, ORC, and columnar storage formats.
Implement schema evolution, auditing, and metadata strategies.
4. Data Warehouse Engineering Design dimensional models: Star Schema and Snowflake Schema.
Build fact and dimension tables supporting analytics and reporting.
Optimize table structures, keys, and partitioning strategies.
5. Databricks (Added Advantage) Develop notebooks/jobs using PySpark/Scala.
Manage clusters, workflows, and Delta Live Tables.
Implement best practices for performance and cost efficiency.
6. SQL Engineering Strong command of SQL for aggregations, analytical functions, joins,profiling, andvalidation.
Write and optimize complex queries supporting dashboards, metrics, and reports.
7. Cloud Data Platforms Azure: Data Factory, Synapse Analytics, ADLS Gen2, Azure Functions (optional).
Snowflake: Virtual Warehouses, Snowpipe, Streams & Tasks, performance tuning.
8. Data Quality & Documentation Validate transformation logic against business rules.
Document data flows, transformation rules, aggregation logic, and data
dictionary/metadata.
Work with QA and analysts to ensure outputs match business expectations.
Required Qualifications
5+ years of hands-on data engineering experience.
Strong programming skills: Spark, Scala, Python.
Strong SQL skills (aggregations, analytical functions, large joins).
Experience with Data Lake and Data Warehouse concepts.
Experience with Spark-based processing (delta optimization, shuffle tuning, partitioning).
Experience with at least one cloud data ecosystem (Azure/AWS/GCP).
Preferred Skills
Experience with Databricks (highly desirable).
Experience with Snowflake or modern cloud DWH.
Experience with ADF/Synapse/Airflow/dbt for orchestration.
Knowledge of CI/CD for data pipelines.
Experience with large-scale data analytics environments.
Soft Skills
Strong understanding of business logic behind analytics outputs.
Ability to translate business metrics into technical transformations.
Strong problem-solving and debugging skills.
Good communication and cross-team collaboration.
See All 39 Data Engineer Jobs in Indiana
Find roles in Indiana that match your experience and apply in just a few clicks.
Find Data Engineer JobsData Engineer Jobs by City in Indiana
Where Indiana roles are concentrated, by current openings.
Data Engineer Job Market in Indiana
A snapshot from current Indiana openings, updated as new roles post.
Who's Hiring
- Speechify3
- HCM2
- Eli Lilly2
- Amazon2
- Steel Dynamics2
Top Industries Hiring
- Technology & Software7
- Healthcare & Medical Services3
- Retail2
- Biotechnology & Pharmaceuticals2
- E-Commerce & Online Marketplaces2
What Indiana Employers Look For
The qualifications that appear most often in data engineer jobs across Indiana.
- Bachelor's degree in computer science, information systems, or a related quantitative field
- Proficiency in SQL and at least one programming language such as Python or Scala
- Experience building and maintaining data pipelines using tools like Apache Spark or Airflow
- Familiarity with cloud data platforms such as AWS, Azure, or Google Cloud
- Knowledge of data warehousing concepts and tools including Snowflake, Redshift, or BigQuery
- Strong collaboration skills for working with data analysts, scientists, and business stakeholders
Data Engineer Jobs in Indiana: Frequently Asked Questions
How do you become a data engineer in Indiana?
Data engineering in Indiana requires no state-issued license or registration. Most employers hire candidates with a bachelor's degree in computer science, information systems, or a related field, combined with demonstrated experience in data pipeline tools and cloud platforms. Indiana universities including Purdue, Indiana University, and IUPUI offer relevant programs. Building a portfolio of pipeline and warehousing projects strengthens applications considerably for Indiana-based roles.
Which companies hire data engineers in Indiana?
Employers hiring data engineers in Indiana right now include Speechify, HCM, and Eli Lilly, based on current listings on Migrate Mate as of July 2026. Indiana's life sciences and healthcare sector, anchored in Indianapolis, generates consistent demand from large systems and pharmaceutical firms alongside growing fintech and insurance employers.
Which Indiana cities have the most data engineer jobs?
Indianapolis, Fort Wayne, and Trivandrum lead Indiana for data engineer openings. Indianapolis dominates because of its dense concentration of healthcare, pharmaceutical, and insurance headquarters, while Fort Wayne and Bloomington draw demand from regional manufacturing operations and Indiana University's research and administrative data infrastructure.
Are there remote data engineer jobs in Indiana?
Yes, and more than most fields. Data engineering is a desk-based, software-driven role that transfers well to remote or hybrid arrangements. About 64% of data engineer openings tied to Indiana are remote or hybrid as of July 2026, reflecting how broadly employers accept distributed teams for this discipline. Pipeline development and cloud architecture work are the sub-areas most commonly offered remotely.
How can I get hired as a data engineer in Indiana with little or no experience?
The most realistic entry path is through an analyst or database administrator role at an Indiana employer and then transitioning internally once you've built pipeline skills. Large Indiana employers in healthcare and insurance regularly hire data analysts and BI developers as entry points. Completing a cloud certification on AWS or Azure, contributing to open-source data projects, and targeting associate data engineer postings at IUPUI-affiliated research units or Indianapolis-based insurers gives candidates without direct experience a credible foundation.
Where can I find and apply to data engineer jobs in Indiana?
You can find and apply to data engineer jobs in Indiana on Migrate Mate, which lists current Indiana openings across industries and experience levels. Search the roles that fit your background and apply directly to the ones that match.
See All 39 Data Engineer Jobs in Indiana
Find roles in Indiana that match your experience and apply in just a few clicks.
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