Data Engineer II

Storage Mart • Columbia, MO

4d • Onsite

About The Position

The Data Engineer II builds, tests, and maintains data ingestion and transformation pipelines in Snowflake, using native tools and SQL-based frameworks. The role includes migrating SnapLogic ETL jobs to Snowflake-native pipelines, validating results against legacy outputs, and helping build a new Snowflake data mart with dimensional models, fact and dimension tables, incremental loading patterns, and documentation.

The position develops integrations that bring data from operational databases, SaaS platforms, APIs, and flat or semi-structured files into Snowflake. It also involves optimizing SQL, warehouses, clustering, and data-loading patterns for cost and performance; implementing quality checks, testing, monitoring, and alerting; and delivering documented, well-modeled datasets to BI, Marketing, and Analytics teams.

The engineer follows and improves development practices such as version control, code review, CI/CD, and environment promotion; supports data security, privacy, governance, and access controls; and maintains lineage, source-to-target mappings, and runbooks. The role works through a prioritized backlog with a manager and stakeholders, communicating progress and blockers. It works directly with the Director of Cloud & Data Engineering, who provides architectural direction and mentorship.

Requirements

• Bachelor's degree in computer science, information systems, software engineering, or a related field, or equivalent practical experience.
• Three or more 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 work with large datasets.
• Practical experience with a cloud data warehouse.
• Working knowledge of data warehousing and dimensional modeling concepts, including star and snowflake schemas, slowly changing dimensions, grain, and surrogate keys.
• Proficiency in Python for data work and comfort using 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 as part of a team 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

• Snowflake experience is strongly preferred; comparable experience with BigQuery, Redshift, Databricks, or Synapse will be considered.
• Direct experience building Snowflake pipelines and transformations, or migrating from a legacy ETL tool such as SnapLogic, Talend, Informatica, Matillion, or SSIS into a cloud-native pattern.
• Snowflake certification (SnowPro Core or Advanced) or a cloud platform certification (AWS or Azure).
• 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 tooling and SQL-based frameworks.
• Migrate SnapLogic ETL jobs to Snowflake-native pipelines, validate parity, reconcile results against legacy outputs, and decommission legacy jobs.
• Contribute to designing and building a Snowflake data mart, including dimensional modeling, fact and dimension tables, incremental loads, and documentation.
• Develop and maintain integrations that load 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 catch pipeline failures and data anomalies.
• Deliver clean, well-documented, well-modeled datasets and troubleshoot data questions for BI, Marketing, and Analytics teams.
• Follow and help 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 broader 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.

Benefits

• Mentorship from senior leaders and exposure to new technologies.
• A supportive and collaborative environment.
• Some flexibility in the standard business-hours schedule and a stated emphasis on work-life balance.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level