5+ years of hands-on Databricks development experience with relevant certifications (proof required).
Proven expertise in building, optimizing, and troubleshooting production-grade ETL pipelines.
Strong experience designing and implementing medallion architecture models (raw, curated, and trusted) within Databricks.
Solid understanding of dimensional data modeling to support BI, enterprise reporting, and single source of truth initiatives.
Requirements:
Design, develop, and maintain complex ETL pipelines in Databricks to ensure scalable, high-performance data integration across multiple source systems.
Implement and optimize medallion architecture in Databricks by establishing raw, curated, and trusted data zones to support enterprise-grade governance and reporting.
Develop and enhance dimensional data models to provide analytics-ready business views and support automated dashboards and KPI reporting.
Collaborate with cross-functional teams to translate operational requirements into technical solutions, identify dependencies, and drive alignment while promoting best practices.
Job description
Requirements:
5+ years of hands-on experience with Databricks development, supported by relevant certifications (proof required).
Proven expertise in building, optimizing, and troubleshooting production-grade ETL pipelines.
Strong experience designing and implementing medallion architecture models (raw, curated, and trusted layers) within Databricks environments.
Solid understanding of dimensional data modeling to support business intelligence, enterprise reporting, and single source of truth initiatives.
Advanced expertise in orchestrating data ingestion, transformation, and integration workflows across multiple systems and data formats.
Ability to interpret operational requirements, convert them into technical solutions, and clearly communicate the business impact of engineering decisions.
Demonstrated ability to take ownership, work independently, and drive projects successfully in dynamic or ambiguous environments.
Experience with Azure Data Lake, Azure Data Factory, and related Azure services is considered a strong plus.
Strong communication and collaboration skills, with the confidence to provide constructive feedback, challenge assumptions, and advocate for best practices.
Ability to adapt quickly, stay results-oriented, collaborate effectively, maintain a positive attitude, and lead with empathy.
Actively contribute to a culture of collaboration, continuous improvement, knowledge sharing, and openness to innovation.
Demonstrated ability to provide meaningful insights and respectfully push back when needed, always focusing on achieving the best possible outcomes for the team and project.
Responsibilities:
Design, develop, and maintain complex ETL pipelines in Databricks, ensuring scalable and high-performance data integration across multiple source systems.
Implement and optimize medallion architecture within Databricks by establishing structured data zones (raw, curated, and trusted) to support governed, enterprise-level reporting.
Develop and enhance dimensional data models that provide analytics-ready business views and support automated dashboards and KPI reporting frameworks.
Collaborate closely with cross-functional teams, including data stewards, IT teams, and business stakeholders, to translate operational requirements into effective technical solutions while proactively identifying dependencies and driving alignment.
Contribute to architectural and technical decisions by recommending best practices, challenging assumptions where necessary, and ensuring the scalability, durability, and flexibility of the data platform.
Proactively identify and resolve integration issues, data quality concerns, and process bottlenecks, while providing actionable insights and constructively highlighting potential project risks or inefficiencies.
Support documentation and knowledge-sharing initiatives to enable teams and clients to independently maintain and enhance data solutions over time.
