Data Engineer II
About The Position
The Data Engineer II builds and maintains Snowflake data pipelines and transformations that support Marketing, BI, Finance, and Operations. The role works directly with the Director of Cloud & Data Engineering, who provides architectural direction and mentorship, while the Data Engineer owns delivery work end to end. The position contributes to a new Snowflake data mart, migrates legacy ETL jobs, and provides well-modeled datasets and support to data consumers. The role also supports performance, data quality, security, privacy, governance, documentation, and engineering practices such as version control, code review, CI/CD, and environment promotion. Work is performed at the company’s home office in Columbia, Missouri. The schedule is primarily standard business hours with some flexibility; after-hours support may be needed.
Requirements
- Bachelor’s degree in computer science, information systems, software engineering, or a related field, or equivalent practical experience.
- At least three years of hands-on experience as a Data Engineer, Analytics Engineer, ETL/BI Developer, or in a similar role.
- Strong SQL skills, including window functions, CTEs, query tuning, and working with large datasets.
- Practical experience with a cloud data warehouse; comparable experience with BigQuery, Redshift, Databricks, or Synapse is considered, with Snowflake strongly preferred.
- Working knowledge of data warehousing and dimensional modeling, including star and snowflake schemas, slowly changing dimensions, grain, and surrogate keys.
- Proficiency in Python for data work and comfort at the command line.
- Experience with semi-structured data such as JSON, including parsing and flattening it into relational structures.
- Experience with cloud platforms such as AWS or Azure, including storage, IAM/access management, secrets, and basic compute.
- Experience with Git and collaborative development workflows.
- Understanding of the needs of BI and reporting tools such as Power BI or Tableau from upstream data models.
- Strong analytical and problem-solving skills, with the ability to work independently and collaboratively in a fast-moving environment.
- Clear written and verbal communication skills, including the ability to explain technical concepts to non-technical stakeholders.
- Willingness to provide after-hours support when needed.
Nice To Haves
- Direct experience building Snowflake pipelines and transformations, or migrating from a legacy ETL tool such as SnapLogic, Talend, Informatica, Matillion, or SSIS to a cloud-native pattern.
- Snowflake certification (SnowPro Core or Advanced) or an AWS or Azure certification.
- Familiarity with data governance and cataloging practices.
- Exposure to analytics and AI/ML platforms and tooling, such as Dataiku, Copilot, or LLM-based tooling in a data context.
- Local candidates or candidates willing to relocate are preferred.
Responsibilities
- Build, test, and maintain Snowflake data ingestion and transformation pipelines using native tools and SQL-based transformation frameworks.
- Migrate SnapLogic ETL jobs to Snowflake-native pipelines, validate parity, reconcile outputs, and cleanly decommission legacy jobs.
- Contribute to the design and buildout of a Snowflake data mart, including dimensional models, fact and dimension tables, incremental loads, and documentation.
- Develop and maintain integrations that bring data from operational databases, SaaS platforms, APIs, and flat or semi-structured files into Snowflake.
- Write performant SQL and tune queries, warehouses, clustering, and load patterns for cost and speed.
- Implement data quality checks, testing, monitoring, and alerting to detect pipeline failures and data anomalies.
- Deliver clean, documented, well-modeled datasets to BI, Marketing, and Analytics teams and troubleshoot data questions.
- Follow and improve engineering practices, including version control, code review, CI/CD for data pipelines, and environment promotion.
- Help uphold data security, privacy, governance, and access-control standards in partnership with the IT team.
- Maintain technical documentation, including data lineage, source-to-target mappings, and runbooks.
- Work through a prioritized backlog with the manager and stakeholders, proactively communicating status and blockers.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
