Sr. Data Engineer, Data Products

Focus on the Family is looking for a senior data engineer to design, build, and optimize certified data products on its enterprise data platform. In this onsite Colorado Springs role, you will help enable ministry reporting, advanced analytics, and AI-enabled data consumption through governed datasets, semantic models, and reliable pipelines.

As a product owner across multiple ministry departments, you will translate recurring reporting needs into reusable, trustworthy data assets that support consistent KPIs for both human and machine consumers.

• Design and build Snowflake-centric solutions including optimized views, data models, and stored procedures for business intelligence, analytics, business operations, and data quality.
• Build and certify semantic views that define ministry metrics, dimensions, and relationships for traditional BI and AI-driven natural language querying (such as Snowflake Cortex Analyst
  ), keeping measures consistent across consumers.
• Create durable, optimized ETL/ELT pipelines for data ingress and egress using SQL and Python
  , including Snowpark and Python stored procedures, in collaboration with the Data Warehouse Manager.
• Implement scheduled automation using Snowflake Tasks
  , Streams
  , or equivalent orchestration tooling to support reliable, hands-off processing.
• Manage database code changes with version control and a defined deployment process, including testing and validation of pipelines and data objects before promoting to production.
• Own assigned certified data products end to end, including definition, documentation, quality tests, versioning, and deprecation so ministry departments can consume them without rework.
• Represent the data product for 5-10 ministry departments
  , translating repeated business questions into certified datasets rather than one-off reports.
• Monitor and optimize Snowflake performance, storage utilization, and query execution.
• Advise on and implement governance standards for least privilege, security, and privacy, including role-based access control, row-level security, and data masking.
• Evaluate and implement Snowflake AI capabilities (for example, Cortex functions for document processing, classification, or forecasting) when there is clear business value, working with data governance stakeholders.
• Follow organizational data privacy and security policies when using AI tools, ensuring no sensitive or regulated data is submitted to external or unapproved AI services.
• Partner with business stakeholders, engineers, and analysts to gather requirements, confirm data product definitions, and align deliverables with ministry reporting needs.
• Support data migration and modernization efforts, including migration from on-premises legacy platforms such as SQL Server and SSRS to the enterprise data platform.
• Identify data processing and data quality issues in collaboration with the Data Quality Analyst.
• Develop technical documentation and apply metadata tagging to communicate lineage, ownership, and approved usage.
• Use AI-assisted development tools (such as Git Hub Copilot and Snowflake Copilot
  ) while retaining full responsibility for validating, testing, and securing AI-assisted output before deployment.
• Perform other duties as assigned.

• Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related field, or equivalent professional experience.
• 5-7 years of data engineering, data warehousing, or business intelligence development experience, including 3+ years building on a cloud data platform (
  Snowflake preferred
  ).
• Advanced SQL experience, including window functions, query optimization, and complex transformations.
• Working proficiency in Python for pipeline development, including Snowpark, stored procedures, or automation scripting.
• Experience designing and building ETL/ELT pipelines
  , including ingestion from external sources (APIs, SFTP, or replication tools such as Fivetran
  ).
• Knowledge of dimensional modeling and semantic layer design, including how upstream modeling impacts downstream reporting and AI consumption.
• Familiarity with role-based access control
  , least-privilege principles, and data security and privacy practices.
• Experience with version control (for example, Git) and structured deployment/change management for database code.
• Experience with a modern BI/analytics platform such as Power BI
  , Tableau
  , Looker
  , or Sigma
  .

• Snowflake
  , Snowpark
  , Python
  , SQL
• Snowflake Tasks
  , Streams
• Snowflake Cortex Analyst
  , Snowflake Cortex
• Git
  , Git Hub Copilot
  , Snowflake Copilot
• Power BI
  , Tableau
  , Looker
  , Sigma
• Fivetran
  , SFTP
  , APIs
• Role-based access control, row-level security, data masking
• AI tools
• SQL Server
  , SSRS
• Metadata tagging

• Snowflake-specific features such as Tasks, Streams, Time Travel, Snowpark, external access integrations, or Cortex AI functions.
• Transformation frameworks such as dbt
  , including model testing, lineage, and CI/CD for analytics code.
• CRM data structures (for example, Salesforce objects and SOQL),…