Teamware Solutions
Website:
teamwaresolutions.net
Company:
https://www.linkedin.com/company/teamware-solutions
Seniority: Associate
Industries: IT Services and IT Consulting
Job details:
Role Overview
Seeking highly skilled Databricks Engineers to join the Data Transformation initiatives. This role requires professionals who can combine strong Databricks engineering expertise with the ability to influence outcomes, collaborate across multiple stakeholder groups, and consistently deliver within aggressive timelines.
The successful candidate will work within a cross-functional delivery pod responsible for building, governing, securing, sharing, and consuming enterprise data products on the Databricks Data Intelligence Platform. As Databricks capabilities continue to evolve rapidly, a strong learning mindset and commitment to continuous upskilling are essential.
Key Responsibilities
Delivery & Stakeholder Management
- Drive successful delivery of workstream objectives within committed timelines.
- Partner with business stakeholders, architects, product owners, data governance teams, and engineering teams.
- Influence technical and business decisions through data-driven recommendations.
- Proactively identify risks, dependencies, roadblocks and drive resolution.
- Participate in sprint planning, technical design reviews, and release activities.
Databricks Engineering
- Design, develop, optimize, and support scalable data pipelines using Databricks.
- Implement Delta Lake, Delta Live Tables, Workflows, Structured Streaming, and Lakehouse architectures.
- Develop data ingestion, transformation, and consumption solutions.
- Build highly performant Spark applications and optimize workloads for cost and performance.
- Implement CI/CD and DevOps practices for Databricks deployments.
- Support production operations and performance tuning.
Unity Catalog & Governance
- Implement and support Unity Catalog migration and adoption.
- Define and manage data governance, access controls, lineage, data classification, and auditing.
- Design enterprise-grade security models using Unity Catalog.
- Enable governed data discovery, sharing, and collaboration across domains.
- Support metadata management, business glossary, domains, metrics, and semantic layers.
Data Sharing & Collaboration
- Design and implement secure data-sharing solutions.
- Leverage Delta Sharing, federated access, and cross-platform data integration capabilities.
- Support enterprise collaboration patterns while ensuring compliance and governance requirements.
- Evaluate and implement emerging Databricks data-serving and Lakebase integration capabilities.
AI, Semantic Layer & Business Consumption
- Develop and support business-facing semantic models and metric views.
- Enable "Talk to Data" experiences using Databricks Genie.
- Support implementation of Unity Catalog Semantics including:
- Domains
- Business Glossaries
- Metrics
- Semantic Models
- Understand and adopt emerging Databricks capabilities including:
- Genie Ontology
- Genie Agents
- Business Semantics
- AI-powered analytics and consumption patterns
Required Technical Skills
Databricks Core
- Strong hands-on experience with:
- Azure Databricks
- Apache Spark (PySpark preferred)
- Delta Lake
- Databricks Workflows
- SQL Warehouses
- Databricks Asset Bundles
- Delta Live Tables (DLT)
- Structured Streaming
Cloud & Data Engineering
- Azure Data Lake Storage (ADLS)
- Azure Data Factory or equivalent orchestration tools
- CI/CD using Azure DevOps or GitHub Actions
- Python, SQL
- Data modeling and dimensional modeling
- Enterprise data warehouse and lakehouse concepts
Unity Catalog & Security
- Unity Catalog administration
- Data governance frameworks
- Access control design
- Data lineage and cataloging
- Row and column level security
- Regulatory and compliance considerations
Analytics & Semantic Modeling
- Semantic data models
- Metric Views
- Business KPIs and analytical modeling
- Databricks Genie
- Data serving and consumption architectures
Preferred Skills
- Experience in large-scale banking or financial services transformation programs.
- Experience with Delta Sharing and federated data access.
- Understanding of Lakebase architecture and application integration patterns.
- Familiarity with GenAI and Databricks AI capabilities.
- Experience implementing enterprise semantic layers and business ontology models.
- Experience with Agile delivery methodologies.
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