Technical Architect - Databricks

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Job Description Databricks Architect
Key Responsibilities:

• Lead the architecture, design, and implementation of end-to-end data solutions on the Databricks Lakehouse Platform.

• Build and optimize scalable data pipelines for structured and unstructured data using Apache Spark on Databricks.

• Define and enforce data engineering and architectural best practices.

• Collaborate with data scientists, analysts, and business stakeholders to understand requirements and translate them into scalable solutions.

• Architect and lead the design of CI/CD pipelines and automation for Databricks Pipelines.

• Ensure data governance, security, and compliance in all solutions.

• Provide technical leadership and mentorship to data engineering teams.

• Evaluate new tools and technologies to continuously improve platform efficiency and performance.

• Work with Azure/AWS/GCP cloud environments integrated with Databricks.

Required Skills & Qualifications:

• 8+ years of hands-on experience with Databricks, including Spark, Delta Lake, MLflow, and DBSQL.

• Strong experience in building large-scale ETL/ELT data pipelines.

• Solid knowledge of data modeling, data warehousing, and distributed computing.

• Experience with cloud platforms (Azure, AWS, or GCP), preferably Azure.

• Proven track record of implementing best practices in data engineering and architecture.

• Proficiency in Python, SQL, and Spark-based processing.

• Strong understanding of DevOps practices in the context of Databricks (CI/CD, infrastructure as code).

• Excellent communication and stakeholder management skills.

Good to Have:

• Experience or working knowledge of Microsoft Fabric.

• Familiarity with Power BI, Synapse Analytics, or other modern BI tools.

• Certifications related to Databricks or Azure (e.g., Databricks Certified Data Engineer, Microsoft Certified: Azure Solutions Architect)