Role Overview :

We are seeking a Director / Associate Director Cloud Engineering (Azure Stack) with a strong specialization in Databricks to lead multiple client engagements, drive end-to-end project delivery, and manage high-performing engineering teams.

This strategic leadership role requires hands-on technical expertise, excellent project and people management skills, and a track record of delivering large-scale data engineering solutions in cloud-native environments.

Responsibilities :

- 14+ years in data engineering, including 3+ years in leadership/director-level roles

- Proven experience with Databricks, Delta Lake, and cloud data architecture

- Strong track record of project delivery, team management, and client success

- Excellent communication and leadership skills in fast-paced environments

- Oversee and deliver multiple Databricks-based data engineering projects

- Manage project budgets, costing, staffing, and client expectations

- Lead and mentor engineering teams across engagements

- Collaborate with clients on architecture, strategy, governance, and reporting

- Ensure high-quality delivery aligned with best practices and business value

Required Skills :

- Strong hands-on experience with Databricks

- Deep hands-on experience with Azure data services

- Strong background in building scalable ETL/ELT pipelines

- Proven experience in designing data warehouses or lakehouses

- Hands-on experience implementing Unity Catalog

- Ability to work with business teams to build dashboards

Qualifications :

- Databricks Full-platform expertise for scalable data solutions : Strong hands-on experience with Databricks for building and managing ETL pipelines, Delta Lake, notebooks, and job orchestration.

- Skilled in cluster optimization, workspace management, and integrating Databricks with Azure services.

- Cloud Azure (preferred), or similar cloud environments : Deep hands-on experience with Azure data services such as Azure Data Lake, Azure Synapse, Azure Data Factory, and integration with Databricks.

- Ability to design and deploy cloud-native data architectures.

- Data Engineering Spark, PySpark, and Python for scalable data processing : Strong background in building scalable, high-performance ETL/ELT pipelines using Spark and PySpark.

- Ability to write optimized, production-grade Python code for data transformation, orchestration, and automation in distributed environments.

- Data Warehousing & SQL Designing and querying enterprise data models : Proven experience in designing data warehouses or lakehouses, dimensional modeling, and writing complex SQL queries for analytics and reporting.

- Governance Implementation and management of Unity Catalog : Hands-on experience implementing Unity Catalog for managing metadata, access control, and data lineage in Databricks.

- Reporting Tools Power BI or similar (Tableau, Looker, etc.)

- Ability to work with business teams to build insightful dashboards and visualizations using Power BI.