System Engineer II

06-Jan-2026

Data Engineer

US Remote

10652

As the recognized global standard for project-based businesses, Deltek delivers software and information solutions to help organizations achieve their purpose. Our market leadership stems from the work of our diverse employees who are united by a passion for learning, growing and making a difference. At Deltek, we take immense pride in creating a balanced, values-driven environment, where every employee feels included and empowered to do their best work.

Our employees put our core values into action daily, creating a one-of-a-kind culture that has been recognized globally. Thanks to our incredible team, Deltek has been named one of America s Best Midsize Employers by Forbes, a Best Place to Work by Glassdoor, a Top Workplace by The Washington Post and a Best Place to Work in Asia by World HRD Congress.

We re seeking a Data Engineer to join our Enterprise Data & Intelligence team during an exciting transformation from a legacy SQL Server enterprise data warehouse to Snowflake as our Enterprise-wide intelligent data platform. You ll play a critical role in building and maintaining data pipelines that not only power today s analytics but also lay the foundation for tomorrow s unified trusted data foundation, self-service analytics, semantic layers, and AI/ML capabilities to enable strategic data capabilities.

This position requires someone who combines strong technical skills with deep understanding of data warehousing fundamentals and the ability to translate complex technical concepts for diverse stakeholders. You ll work on everything from pipeline development to transformation logic in dbt, ensuring our intelligent data platform delivers reliable, well-structured data that empowers both traditional reporting and advanced analytics use cases.

• Design, develop, and maintain data pipelines that feed our Snowflake intelligent data platform using Python, Fivetran, and other modern ETL/ELT tools
• Build and maintain transformation logic in dbt, converting SQL Server stored procedures to modular, testable dbt models on Snowflake
• Develop dimensional data models following best practices, creating the foundation for semantic layers and self-service analytics
• Translate complex SQL Server stored procedures and SSIS packages from our legacy EDW database to dbt models and cloud-native solutions
• Implement proper grain definition, ensure additivity of facts, and maintain dimensional consistency across data marts to support both BI and future ML workloads
• Create dbt tests, documentation, and lineage to ensure data quality and transparency
• Partner with analytics teams, business stakeholders, and subject matter experts across the enterprise to understand requirements, validate business logic, and translate them into robust technical solutions that scale with our platform s intelligence capabilities
• Develop and enforce data quality standards that ensure our platform remains trustworthy for both human and AI consumers
• Contribute to our migration strategy from traditional EDW database to intelligent data platform architecture through analytical problem-solving and strategic thinking
• Containerize data applications using Docker and deploy to Kubernetes environments
• Facilitate knowledge transfer sessions and documentation to ensure the entire team understands new patterns and approaches

Technical Skills

• Strong SQL expertise with ability to write complex, optimized queries and understand execution plans
• Snowflake experience including understanding of virtual warehouses, micro-partitions, and cloud data warehouse best practices
• dbt proficiency including:
  • Building modular, reusable data models
  • Writing custom tests and macros
  • Understanding materializations (tables, views, incremental models)
  • Documentation and lineage best practices
  • Converting stored procedure logic to dbt models
• Python proficiency for data engineering tasks (pandas, SQL Alchemy, pipeline orchestration)
• Deep understanding of dimensional modeling and data warehousing fundamentals including:
  • Fact and dimension table design patterns
  • Slowly changing dimensions (Type 1, 2,
    3)
  • Grain…