Vation Ventures
Senior Data Engineer
Denver, Colorado, USA · Senior · full-time
Sponsorship not specified$150k-$165kDetected 94 days ago
PythonSQLSnowflakeDatabricksAWSGCPAzureCloud PlatformsCI/CDKafkaSparkAirflowdbtData EngineeringData VisualizationRAGSalesforceSAPUnity
About the role
- This is a hands-on role with architecture leadership.
- The tooling is the easy part; the hard part is the reasoning.
Responsibilities
- Senior Data Engineer Introduction We''re hiring a Senior Data Engineer to lead data platform delivery across our client engagements.
- This role involves architecting lakehouses, building production pipelines, modeling for analytics and AI workloads, and handing off platforms clients can actually operate.
- You''ll spend most of your time in code - building Lakeflow pipelines, dbt models, and ingestion patterns - but you''ll also make the calls that shape the platform: Bronze/Silver/Gold structure, medallion vs. hub-and-spoke, catalog design, governance model.
- You''ll walk into messy client environments - legacy core systems, undocumented schemas, competing definitions of "customer" across three departments - and figure out what to actually build.
- You''ll scope, design, build, and present.
- Own data platform delivery on concurrent client engagements Design lakehouse and warehouse architectures across Databricks, Snowflake, and Microsoft
- Lakeflow SDP (formerly DLT), Spark SQL, PySpark, dbt, Snowpark Design Unity Catalog and governance structures that hold up at enterprise scale Model for both analytics and AI workloads - dimensional models for BI, feature-ready data for retrieval and agents Reverse-engineer legacy sources (SAP, Salesforce, Oracle, proprietary core systems) with incomplete documentation and build ingestion that doesn''t break
Requirements
- 5-8 years of data engineering experience with a focus on production platforms that serve real users Deep experience across all three major lakehouse/warehouse platforms: Databricks, Snowflake, and Microsoft Fabric.
- Databricks, Snowflake, and Fabric all have a right answer somewhere - you know which is which and why.
- You know when to reach for a streaming pipeline and when a nightly batch is the right answer.
- You can hold the full system in your head - sources, ingestion, storage, transformation, semantic layer, consumption - and reason across all of them simultaneously.
- Required Skills 5-8 years of data engineering experience with a focus on production platforms that serve real users
Nice to have
- data quality, lineage, observability, cost, CI/CD Client-facing presence.
Compensation
- $150k-$165k
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