Data Engineer 1
Big Data
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Cloud Data Engineering
Cloud Data Platform
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Cloud Native
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Data
Data Analysis
Data Analytics
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SQL
Job Description
Entry-level Data Engineer role on Kiewit’s Data Platform team, supporting the build, testing, and ongoing maintenance of pipelines that deliver analytics-ready data.
Responsibilities
- Develop and maintain SQL transformations and Python scripts for data ingestion and transformation workflows
- Support ETL/ELT pipeline development and testing under the direction of senior engineers
- Participate in code reviews, documentation, and testing practices to help keep data trustworthy
- Collaborate with analysts, data architects, and business stakeholders to clarify data requirements and troubleshoot issues
- Learn and apply the data stack, including a cloud lake house, orchestration, and transformation tooling
- Identify blockers, ask questions, and propose solutions as part of a collaborative team
Requirements
- 0–3 years of relevant experience (internships, academic or personal projects, or early-career data, analytics, or software work)
- Demonstrable internship or coursework experience working with data, analytics, and business stakeholders
- Degree in Computer Science / Computer Science & Engineering, Data Science, or similar
- SQL proficiency including basic joins, aggregations, and database normalization concepts
- Python (or similar): comfortable writing scripts, using libraries such as pandas, and understanding functions/OOP basics
- Git/GitHub experience from class projects or personal repositories; understands branches and PRs conceptually
- High-level understanding of data pipelines including ETL/ELT and batch vs. streaming concepts
- Comfort using the command line and navigating basic cloud/dev environments
- Strong written communication skills for documentation and async collaboration
Preferred Qualifications
- Exposure to a cloud platform such as Azure or GCP
- Familiarity with modern data tooling such as Databricks, dbt, or Snowflake
- Experience with data quality or testing frameworks
- Coursework or project experience involving data warehousing or dimensional modeling
Required Work Conditions
- Maintain 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, following oral and written instructions, including warning signs, equipment use, and other policies
- Work during normal operating hours; overtime and weekends as required
Technologies
- SQL, Python, pandas
- Git, GitHub
- ETL, ELT
- Cloud lake house, orchestration, transformation tooling
- Azure, GCP
- Databricks, dbt, Snowflake
Benefits
- 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
- Generous paid time off
Location
- Omaha, NE (onsite)
- Based out of 12312 Port Grace Blvd, La Vista, NE 68128
- Not remote or hybrid
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