KX is hiring a Lead Snowflake Data Engineer to join a lean, four-person Enterprise Applications team reporting into the Head of Enterprise Applications. This is the critical hire that takes ownership of Snowflake as an internal capability, inheriting an in-progress implementation from third-party partners, validating what’s been built, and carrying the platform forward towards a single Business 360 view unifying Finance, Revenue, and People data. This is a hands-on, end-to-end role spanning ingestion through to certified metrics, with direct exposure to senior leadership and a mandate to shape how KX uses data and AI to make faster, more accurate decisions.
Essential Experience
Preferred Qualifications
Requirements
- Own data ingestion pipelines into Bronze through Workato, and maintain the full Medallion stack: Bronze (raw), Silver (cleansed), Gold (dimensional models and marts), and Platinum (semantic layer and certified metrics)
- Deliver data governance across all Medallion layers: RBAC with least-privilege access, dynamic data masking, column-level security, data catalogue, business glossary, and lineage from source to semantic layer, aligned to GDPR, SOC 2, and ISO 27001
- Implement data quality and observability: tests, freshness SLAs, anomaly detection, alerting, and clear escalation paths when issues arise
- Drive the Snowflake capability roadmap: evaluate and pilot dynamic tables, streams and tasks, Snowpark, Cortex, and Marketplace; identify where Cortex and LLM functions can reduce manual effort for business users within KX’s AI governance framework
- Manage platform performance, cost, and reliability: sizing, clustering, materialisation, and query tuning, and maintain documentation, lineage, and standards for everyone who works with Snowflake
- Sit on the Data Governance Work Group (chaired by the CIO), contributing to data ownership, metric certification, and schema change approvals
Responsibilities
Skills- Advanced SQL and Python: 5+ years of production experience in an analytics or data engineering context
- Deep dimensional modelling (Kimball: facts, dimensions, SCDs, conformed dimensions) with a clear understanding of how each fits in a Medallion architecture
- Production dbt experience: model design, tests, macros, snapshots, and a clear point of view on project structure; dbt Cloud familiarity is a plus
- Hands-on experience building and maintaining a Platinum-tier semantic layer that non-technical users can rely on
- GitLab proficiency: branching, merge requests, and CI/CD for dbt and SQL
- Strong communication: able to align a CFO, a sales ops lead, and an HR analyst on a shared data definition before building anything
- Genuine curiosity about AI: specifically what Snowflake Cortex and LLM functions can and can’t do, and when to reach for them
Essential Experience
- Practical data governance delivery: hands-on implementation of RBAC, column-level security, dynamic data masking, and encryption in a cloud data platform; experience building or maintaining a data catalogue and business glossary, defining data classification and retention policies, and evidencing lineage from ingestion to reporting
- Regulatory context awareness: understands GDPR and SOC 2 at minimum, and knows how to operationalise governance without it becoming a blocker; comfort enforcing an existing data classification scheme (restricted / confidential / classified) rather than inventing one
- Working knowledge of L2C, R2R, H2R, and SaaS metrics (ARR, NRR, bookings vs revenue)
Preferred Qualifications
- Familiarity with BI tools consuming Gold and Platinum models (Power BI, Tableau)
- Snowflake certifications (SnowPro Core or Advanced)
- Background in lean environments where ownership is wide and titles are loose