Data Platform Engineer: ETL/ELT Pipelines

Kiewit Corporation; Lenexa (KS); On-site; USD 110,000 - 150,000; Full time

Job summary

Kiewit Corporation seeks a Data Engineer to develop ELT/ETL pipelines moving data from source apps to data platforms for reporting and analytics. You will work on campus with Lenexa, Kansas or Omaha, Nebraska attendance.

The role emphasizes building scalable data solutions across lakehouse architectures, using Databricks, Spark, Snowflake and dbt, with CI/CD practices and on-site collaboration with cross-functional teams.

Qualifications

• 3+ years of experience in data engineering, analytics engineering, software engineering, or related discipline.
• Advanced experience with Python and SQL.
• Experience designing and operating scalable batch or streaming data pipelines.
• Strong understanding of data lake, lakehouse, cloud data warehouse, and dimensional data modeling concepts.
• Experience with Microsoft Azure, Databricks, and Snowflake.
• Experience with Dagster and dbt.
• Understanding of distributed data processing, partitioning, schema evolution, and performance optimization.
• Experience implementing automated testing, monitoring, alerting, and operational controls for production data systems.
• Familiarity with source control, pull-request reviews, CI/CD, and automated deployment practices.
• Ability to lead technical discussions and communicate complex topics clearly to technical and nontechnical audiences.

Responsibilities

• Build and support data pipelines that ingest, transform, validate, and publish data for analytics and enterprise data products.
• Implement data solutions across lakehouse, data lake, and cloud data warehouse platforms following established architecture and design patterns.
• Develop reusable datasets and data transformations using Databricks, Spark, Snowflake, and dbt.
• Follow team standards for data modeling, coding, testing, documentation, monitoring, and deployment.
• Configure and support scheduled data workflows using JAMS, Dagster, or similar orchestration platforms.
• Implement data-quality checks for completeness, accuracy, freshness, schema changes, and business rules.
• Profile source data and collaborate with data modelers, DBAs, and technical leads to identify data structures, performance needs, and required database changes.
• Apply Git-based development and established CI/CD practices to develop, test, document, schedule, and deploy data pipelines.
• Contribute to data platform practices for security, governance, metadata, lineage, reliability, and recovery.
• Work with product owners, architects, platform engineers, analysts, data scientists, and business stakeholders to translate requirements into maintainable data solutions.
• Coordinate with data producers and consumers to clarify data requirements, dependencies, ownership, and expectations.
• Produce and maintain solution documentation as a standard deliverable, including data flows, transformation logic, dependencies, operational procedures, and support guidance.
• Troubleshoot production issues, support business-critical workflows, and document findings and resolutions to help prevent recurring problems.
• Participate in production support, on-call duties, agile delivery activities, and post-deployment knowledge sharing.
• Participate in design and code reviews, incorporating feedback to improve the quality, performance, and maintainability of data solutions.
• Share technical knowledge with teammates and contribute to team learning and continuous improvement.
• Evaluate tools and approaches relevant to the team’s data platform, and recommend improvements through established technical review processes.
• Use AI-assisted development tools responsibly to support engineering, testing, and documentation.

Skills

Python

SQL

Data pipelines

ETL/ELT

Databricks

Spark

Snowflake

dbt

Dagster

Azure

CI/CD

Git

Tools

Databricks

Spark

Snowflake

dbt

Dagster

Airflow

Azure DevOps

GitHub Actions

Job description

Kiewit Corporation seeks a Data Engineer to develop ELT/ETL pipelines moving data from source apps to data platforms for reporting and analytics. You will work on campus with Lenexa, Kansas or Omaha, Nebraska attendance.

The role emphasizes building scalable data solutions across lakehouse architectures, using Databricks, Spark, Snowflake and dbt, with CI/CD practices and on-site collaboration with cross-functional teams.