Position listed on behalf of a partner company managing applications
Collaborative consulting environment across diverse industries
Responsibilities
Lead data architecture and solution design using Databricks, Lakehouse architecture and medallion design patterns
Define and execute data strategies, assess existing environments and develop roadmaps
Drive data engineering and platform modernization: pipelines, ETL, data warehouses, integration and modeling
Implement Databricks solutions: Apache Spark, PySpark, Spark SQL, Delta Lake, Auto Loader, Lakeflow Declarative Pipelines, Databricks SQL and workflow orchestration
Promote automation, CI/CD and environment management via Databricks Asset Bundles and Git integration
Strengthen data governance and security using Unity Catalog for lineage, access permissions and data sharing
Optimize platform performance: pipelines, queries, models, compute resources and cost
Lead client engagements, project delivery and quality reviews
Build strong client relationships and communicate value through data storytelling
Develop and mentor high-performing teams
Drive business development, proposals and pursuit activities
Stay informed on data engineering, cloud architecture, analytics, ML and generative AI
Requirements
Bachelor's degree in Management Information Systems, Computer Information Systems, Analytics or related discipline
At least 7 years of experience in professional services, technology consulting, data engineering or related industry
Required Databricks Certified Data Engineer Professional or Databricks Certified Machine Learning Professional; Databricks Champion preferred
Experience designing modern data platforms and enterprise data architectures using Databricks
Strong knowledge of data movement, integration, transformation, cleansing, ETL, data warehousing and data modeling (entity-relationship, dimensional, semantic)
Experience with Databricks and Apache Spark technologies
Conditions
Hybrid position balancing remote work, in-person collaboration and client engagement