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Engineer Manager
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Added 1 min ago
Staff Data Engineer - Databricks
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Senior Program Manager & Key Client Lead, Data Centers
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- $150,000 to $225,000 USD / year
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Added 6 mins ago
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Senior Program Manager & Key Client Lead, Data Centers
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Boston, Massachusetts, MA
- $150,000 to $225,000 USD / year
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Added 6 mins ago
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Senior Program Manager & Key Client Lead, Data Centers
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Syracuse, New York, NY
- $150,000 to $225,000 USD / year
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Added 6 mins ago
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Senior Program Manager & Key Client Lead, Data Centers
Ramboll
Chicago, Illinois, IL
- $150,000 to $225,000 USD / year
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Added 6 mins ago
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Senior Program Manager & Key Client Lead, Data Centers
Ramboll
Houston, Texas, TX
- $150,000 to $225,000 USD / year
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Kiewit

Data Engineer

Omaha, NE, United States
Lenexa, KS, United States

Full-time

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Job details

Job type: Full-time
Apply by: May 15, 2027
Experience: · 3+ years of experience in data engineering, analytics engineering, software engineering, or a related discipline, or equivalent practical experience.
Posting language: English
Posted: Nov 4, 2026

Original job description

Requisition ID: 182999

Job Level: Mid Level

Home District/Group: DHO Information Technology Group

Department: Technology Group

Market: Corporate Home Office

Employment Type: Full Time

Position Overview

The Data Engineer is responsible for the development of ELT/ETL packages and scripts to move data from source applications to data Platforms for Reporting and Analytic functions

District Overview

Kiewit Technology Group builds solutions to enable and support our company's expansive operations. Our mission is to deliver project schedule and cost certainty by employing technology designed by and for the construction industry. Our team utilizes systems and tools that manage every part of Kiewit's business and the project lifecycle to improve planning and day-to-day execution in the field. We give our people real-time data to make faster, smarter decisions.

Location

This role is located on our Lenexa, KS or Omaha, NE campus and requires regular on site attendance.

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 technologies such as 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.

Qualifications

· 3+ years of experience in data engineering, analytics engineering, software engineering, or a related discipline, or equivalent practical experience.

· Advanced experience with Python and SQL.

· Demonstrated 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, or demonstrated ability to quickly learn, Microsoft Azure, Databricks, and Snowflake.

· Experience with, or strong interest in learning, Dagster and dbt.

· Understanding of distributed data processing, data 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.

· Demonstrated ability to work effectively across engineering, analytics, security, governance, and business teams.

· Strong problem-solving, ownership, prioritization, and decision-making skills.

Preferred Qualifications

· Experience developing analytics solutions with dbt, including testing, documentation, deployment, and model optimization.

· Experience building or operating workflows with Dagster, Airflow, or a comparable orchestration platform.

· Experience with Azure DevOps or GitHub-based CI/CD workflows.

· Experience with Grafana or similar monitoring and observability platforms.

· Experience supporting data platforms in secure or large-enterprise environments.

· Experience using AI-assisted software engineering tools securely and effectively.

· Demonstrated experience mentoring engineers or leading technical initiatives.

Other Requirements:

Regular, reliable attendance
Work productively and meet deadlines timely
Communicate and interact effectively and professionally with supervisors, employees, and others individually or in a team environment.
Perform work safely and effectively. Understand and follow oral and written instructions, including warning signs, equipment use, and other policies.
Work during normal operating hours to organize and complete work within given deadlines. Work overtime and weekends as required.
May work at various different locations and conditions may vary.

We offer our fulltime staff employees a comprehensive benefits package that’s among the best in our industry, including top-tier medical, dental and vision plans covering eligible employees and dependents, voluntary wellness and employee assistance programs, life insurance, disability, retirement plans with matching, and generous paid time off.

Equal Opportunity Employer, including disability and protected veteran status.

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More about this job

Skills

Data engineering
Reporting
Data warehouse
Databricks
Apache Spark
Snowflake
dbt
Data modelling
Documentation
Statistical quality control
Git
CI/CD
Troubleshoot
Process improvement
Python
SQL
Microsoft Azure
Process data
Test automation
Problem solving
Prioritization
Decision making
Apache Airflow
DevOps
GitHub
Grafana
Coaching
Meet deadlines

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