Requisition ID: 182311
Job Level: Senior Level
Home District/Group: DHO Information Technology Group
Department: Technology Group
Market: Corporate Home Office
Employment Type: Full Time
Position Overview
Kiewit Technology Group is building a modern and scalable data platform to support enterprise analytics and significantly expand Kiewit's use of artificial intelligence and machine learning.
We are hiring a Senior Data Engineer to design, build, and operate reliable data pipelines, curated datasets, and reusable platform capabilities. These solutions will support reporting, advanced analytics, AI and machine learning applications, and business-critical data products across Kiewit.
The ideal candidate will combine strong data engineering fundamentals with technical leadership, sound architectural judgment, and a collaborative mindset. We value candidates who can establish engineering standards, mentor others, solve complex platform challenges, and quickly learn emerging cloud and lakehouse technologies.
District Overview
Kiewit Technology Group helps make Kiewit a data-driven organization by delivering trusted data, scalable data products, and modern platform capabilities that support teams across the business.
Location
This position offers flexible work arrangements and may be performed remotely within the Atlanta, GA metro area. Occasional travel may be required for team meetings and planning sessions.
Responsibilities
- Design, build, and support scalable data pipelines that ingest, transform, validate, and publish data for analytics, AI, machine learning, and enterprise data products.
- Lead the technical design of complex data solutions across lakehouse, data lake, and cloud data warehouse platforms.
- Develop well-structured, reusable, and tested datasets using technologies such as Databricks, Spark, Snowflake, and dbt.
- Define and promote engineering standards for data modeling, coding, testing, documentation, monitoring, and deployment.
- Design orchestration patterns and monitor production workflows using Dagster or similar orchestration platforms.
- Build automated data-quality controls covering completeness, accuracy, freshness, schema changes, and business-rule validation.
- Optimize distributed data processing, table design, SQL queries, storage, and compute resources for performance and cost efficiency.
- Implement CI/CD pipelines and Git-based development practices for data pipelines, infrastructure, orchestration, and analytics code.
- Contribute to platform architecture decisions involving scalability, security, governance, metadata, lineage, reliability, and disaster recovery.
- Partner with architects, platform engineers, analytics teams, data scientists, and business stakeholders to translate requirements into maintainable data solutions.
- Establish data contracts and clear ownership expectations with upstream data producers and downstream consumers.
- Lead troubleshooting and root-cause analysis for complex production incidents and implement measures to prevent recurrence.
- Participate in production support and on-call responsibilities for business-critical data products.
- Mentor engineers through design reviews, code reviews, technical guidance, and knowledge-sharing sessions.
- Evaluate new technologies and recommend improvements aligned with Kiewit's long-term data platform strategy.
- Use AI-assisted development tools responsibly to improve engineering productivity, testing, documentation, and solution quality.
Qualifications
- 10+ years of experience in data engineering, analytics engineering, software engineering, or a related field, or equivalent practical experience.
- Advanced experience with Python and SQL in production environments.
- Proven experience designing and supporting scalable batch and/or streaming data pipelines.
- Strong knowledge of data lakes, lakehouses, cloud data warehouses, and dimensional data modeling.
- Experience with or ability to quickly learn Azure, Databricks, and Snowflake.
- Experience with or interest in learning dbt and Dagster.
- Understanding of distributed data processing, data partitioning, schema evolution, and performance optimization.
- Experience implementing testing, monitoring, alerting, and operational controls for production data systems.
- Familiarity with source control, code reviews, CI/CD, and deployment automation.
- Strong communication skills with the ability to explain technical concepts to both technical and non-technical audiences.
- Ability to collaborate effectively across engineering, analytics, security, governance, and business teams.
- Strong problem-solving, prioritization, ownership, and decision-making skills.
Preferred Qualifications
- Experience with Apache Spark and lakehouse technologies such as Delta Lake or Apache Iceberg.
- Experience with Databricks Unity Catalog, governance, lineage, access controls, and external locations.
- Experience building analytics solutions using dbt, including testing, documentation, deployment, and optimization.
- Experience with workflow orchestration tools such as Dagster, Airflow, or similar platforms.
- Familiarity with Infrastructure as Code tools, including Terraform.
- Experience with Azure DevOps or GitHub-based CI/CD workflows.
- Experience with Grafana or similar monitoring and observability tools.
- Experience implementing data quality frameworks and data contracts.
- Familiarity with event-driven or streaming architectures.
- Experience supporting enterprise-scale, secure data platforms.
- Experience enabling data products for machine learning, generative AI, or advanced analytics.
- Experience using AI-assisted software development tools responsibly and effectively.
- Experience mentoring engineers and 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.