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Databricks Engineer Jobs in Iowa (NOW HIRING)

... Databricks Data Engineer Associate] is a plus - Designing and implementing thorough data architecture strategies - Developing and documenting data models, data flow diagrams, and data architecture ...

Data Engineer

Johnston, IA · On-site +1

$60 - $75/hr

Job#: 3028821 Data Engineer Location: Johnston, Iowa (Remote) Employment Type: Contract Role ... Hands-on expertise with big data technologies such as Databricks Spark. Extensive experience with ...

Azure Solutions Architect Expert, Azure Data Engineer Associate, Snowflake Core, Snowflake Databricks Data Engineer Associate] is a plus - Proficient in Python and structured/unstructured data ...

... Architect, Databricks Data Engineer Associate] is a plus - Designing and implementing thorough data architecture strategies - Developing and documenting data models and data flow diagrams ...

... Databricks Data Engineer Associate] is a plus - Designing and implementing thorough data architecture strategies that meet the current and future business needs - Developing and documenting data ...

... like Databricks, Snowflake, Python, DataOps, AtScale and Streamsets, etc. You will be part of ... As a Quality Engineer you will plan and conduct a wide range of software quality tests and analyzes ...

Strong SQL and data modeling skills with experience in Snowflake, BigQuery, or Databricks. * Proven ability to design scalable, secure, high-performing Tableau solutions. * Familiarity with Agile ...

Senior Data Architect

West Des Moines, IA · On-site

$61.75 - $82.50/hr

Collaborate with engineers to implement architectural patterns in production systems * Ensure ... Azure Databricks or Microsoft Fabric * Advanced SQL skills and experience with Python (preferred)

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Databricks Engineer information

See Iowa salary details

$55.9K

$104.9K

$190.7K

How much do databricks engineer jobs pay per year?

As of May 30, 2026, the average yearly pay for databricks engineer in Iowa is $104,852.00, according to ZipRecruiter salary data. Most workers in this role earn between $75,600.00 and $124,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Databricks Engineer, and why are they important?

To thrive as a Databricks Engineer, you need strong expertise in big data processing, cloud platforms (like AWS or Azure), and proficiency with languages such as Python, SQL, and Scala, often supported by a degree in computer science or a related field. Familiarity with Apache Spark, Databricks Workspace, version control systems like Git, and relevant Databricks certifications are typically required. Strong analytical thinking, collaboration, and effective communication skills help you understand business needs and work seamlessly with data teams. These skills ensure efficient data pipeline development, scalable analytics solutions, and successful integration of Databricks into organizational workflows.

What are some common challenges faced by Databricks Engineers when working with large-scale data pipelines?

Databricks Engineers often encounter challenges related to optimizing the performance and reliability of large-scale data pipelines. These can include efficiently managing cluster resources, handling data partitioning to prevent bottlenecks, and troubleshooting job failures due to resource constraints or data quality issues. Collaboration with data scientists, analysts, and DevOps teams is essential to ensure seamless integration and deployment of production workflows. Staying current with evolving Databricks features and best practices also plays a key role in overcoming these challenges.

What is a Databricks Engineer?

A Databricks Engineer is a data engineering professional who specializes in using the Databricks platform to build, manage, and optimize data pipelines and analytics solutions. They work with big data technologies like Apache Spark, Delta Lake, and cloud services to process and analyze large datasets efficiently. Their role often involves developing ETL (extract, transform, load) workflows, setting up data lakes, and ensuring data quality and performance for business intelligence and machine learning applications.

How much does a Databricks engineer make?

A Databricks engineer's salary typically ranges from $100,000 to $150,000 annually, depending on experience, location, and skill level. Senior roles or those with specialized skills in Spark, cloud platforms, and data engineering may earn higher compensation. Salaries can also vary based on industry demand and certifications.
What are popular job titles related to Databricks Engineer jobs in Iowa? For Databricks Engineer jobs in Iowa, the most frequently searched job titles are:
What job categories do people searching Databricks Engineer jobs in Iowa look for? The top searched job categories for Databricks Engineer jobs in Iowa are:
Infographic showing various Databricks Engineer job openings in Iowa as of May 2026, with employment types broken down into 2% As Needed, 81% Full Time, 7% Part Time, 6% Contract, and 4% Nights. Highlights an 22% Physical, and 78% Remote job distribution, with an average salary of $104,852 per year, or $50.4 per hour.
Analytics & BI Spclst 3 or Sr

Analytics & BI Spclst 3 or Sr

Berkshire Hathaway Energy

Des Moines, IA • On-site

Full-time

Posted 7 days ago


Berkshire Hathaway Energy rating

6.5

Company rating: 6.5 out of 10

Based on 18 frontline employees who took The Breakroom Quiz


Job description

This is a multi-level posting. Candidates may be considered for any of the posted levels, depending on their level of experience and depth of expertise.

You will design, build, and maintain scalable data pipelines and infrastructure to support analytics, reporting, and data science initiatives. You will work closely with cross-functional teams to ensure data is accessible, reliable, and secure across the organization.

MidAmerican Energy Company, a Midwest utility, provides regulated electric and natural gas service to more than 1.6 million customers in Illinois, Iowa, Nebraska and South Dakota. The company owns and operates a portfolio of power-generating assets, approximately 61% of which is wind generation.MidAmerican Energy Company is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion or religious creed, age, national origin, ancestry, citizenship status (except as required by law), gender (including gender identity and expression), sex (including pregnancy), sexual orientation, genetic information, physical or mental disability, veteran or military status, familial or parental status, marital status or any other category protected by applicable local, state or U.S. federal law. Employees must be able to perform the essential functions of the position, with or without an accommodation.

Bachelor's degree in information systems, computer science or related technical field; or equivalent work experience. (Typically four years of related, progressive work experience would be needed for candidates applying for this position who do not possess a bachelor's degree.) 

Six or more years of experience with advanced knowledge of data architecture, cloud platforms (especially Azure), and enterprise data solutions is required for the sr level.

Proficiency in data engineering tools and platforms, especially Azure Data Factory and Azure Databricks, Informatica Power Center and IICS,  Oracle Data Integrator.

Proficiency in Oracle DB, IBM DB2, Azure. 

Strong understanding of data modeling, ETL/ELT processes, and performance tuning of enterprise-level applications.

Expert-level knowledge of data-related technologies from architecture to administration, including design, development, optimization, and licensing.

Proven experience working in the utility industry is required

Effective oral and written communication skills, with the ability to collaborate across teams and mentor junior engineers.

Strong analytical and problem-solving abilities.

Ability to prioritize and manage multiple tasks and projects concurrently.

  • Design and implement scalable data ingestion and transformation frameworks using one or more of the following:
    •  Azure services enabling structured, semi-structured, and unstructured data to be efficiently processed and integrated into enterprise data platforms
    • Informatica Power Center &  Informatica Cloud
    • Oracle Data Integrator
  • Build and maintain robust ETL/ELT pipelines.
  • Integrate data from diverse sources including on-premises systems, cloud storage, APIs, and streaming platforms.   

Informatica Development and Optimization

  • Design, develop, test, and maintain ETL pipelines using Informatica PowerCenter, including performance tuning, error handling, and integration with ControlM scheduling.
  • Participate in the migration from PowerCenter to Informatica Cloud (IICS) by redesigning mappings, optimizing transformations, and supporting secure agent configurations.

Oracle Data Integrator

  • Design, develop, test, and maintain ETL pipelines using Oracle Data Integrator, including performance tuning, error handling, and integration with ControlM scheduling.
  • Experience with Fusion AI Data Platform a plus  (Fusion Data Intelligence, Fusion Analytics Warehouse).

Databricks Development and Optimization

  • Develop and optimize notebooks and workflows in Azure Databricks using PySpark, SQL.
  • Implement Delta Lake for efficient data storage, versioning, and ACID transactions.
  • Leverage Databricks features such as Unity Catalog and job orchestration.

Data Modeling and Architecture

  • Design and implement data models (star/snowflake schemas) for analytics and reporting.
  • Collaborate with architects to define data lakehouse architecture and best practices.
  • Hands-on experience implementing and optimizing data solutions using the Medallion Architecture (Bronze, Silver, Gold layers) for scalable and structured data processing

  Data Quality and Governance

  • Implement data validation, profiling, and cleansing routines.
  • Ensure compliance with data governance policies, including data lineage and metadata management.

Performance Tuning and Monitoring

  • Monitor and optimize performance various data processes.
  • Troubleshoot and resolve issues related to data latency, job failures, and resource utilization.

Collaboration and Stakeholder Engagement

  • Work closely with data scientists, analysts, and business units to understand data requirements.
  • Translate business needs into technical solutions that are scalable and maintainable.

Security and Compliance

  • Implement role-based access control (RBAC), encryption, and secure data handling practices.
  • Ensure compliance with industry regulations (e.g., NERC CIP, GDPR, HIPAA if applicable).

Documentation and Best Practices

  • Maintain clear documentation of data flows, architecture, and operational procedures.
  • Promote best practices in code versioning, testing, and CI/CD for data engineering.

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