Senior Databricks Engineer

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.
• Proactively identify dependencies and drive alignment across teams to ensure smooth execution.
• 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.