Data Engineer-Kiewit Nuclear Solutions

Company: Kiewit Corporation

Location: Remote (Remote)

Salary: $136,000 - $142,000 a year

Type: Full-time

Remote: Yes

Posted: 2026-04-01

About this role

Requisition ID: 180210

Job Level: Mid Level

Home District/Group: Kiewit Nuclear Solutions

Department: Technology Group

Market: Nuclear

Employment Type: Full Time

## Position Overview

The Technical Systems Analyst / Data Engineer supports enterprise-scale project data platforms that power analytics, reporting, and application integration across Kiewit’s business. This role operates within the Digital Project Execution (DPE) team and is responsible for designing, building, and optimizing modern data pipelines and cloud-based data architectures.

This position combines hands-on data engineering with cross-functional collaboration. The individual will work closely with Project Managers, Digital Execution Managers, Product Managers, Architects, Business Analysts, and core Technology teams to deliver reliable, scalable, and high-performance data solutions.

The ideal candidate is both technically strong / business-aware, and capable of translating complex project workflows into durable, well-architected data systems.

## District Overview

This position is within the Kiewit Technology Group, supporting Kiewit Nuclear Solutions.

## Location

This is a remote position that may require some travel.

#LI-LH1

## Responsibilities

Data Engineering & Architecture

  • Design, build, and maintain scalable ETL/ELT pipelines using Azure Databricks (PySpark, Spark SQL) as the primary platform.
  • Develop and optimize batch, streaming, and micro-batch processing architectures.
  • Implement data ingestion workflows using Azure Data Factory, Azure Data Lake, SQL Server, and Snowflake.
  • Design data models that support analytics, reporting, and database-driven application integration.
  • Optimize performance of large-scale data systems, including query tuning and workload optimization.

Platform & Operations

  • Support day-to-day operations of enterprise data platforms.
  • Troubleshoot end-to-end data pipeline issues across ...

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