The Director of Data Engineering will hold end-to-end accountability for leading, managing, and delivering multiple high-impact data engineering client engagements. This role requires an executive leader with deep hands-on expertise across Azure and Databricks who can drive technical architecture, govern engagement delivery, oversee project P&L;/margins, and mentor high-performing engineering teams. You will bridge technical depth with executive client management to deliver enterprise-grade Lakehouse and modern data platform solutions.

Key Responsibilities

Multi-Engagement Delivery & Governance

- Own end-to-end delivery accountability across concurrent enterprise data engineering programs from inception, scoping, architecture, and sprint execution through production deployment and hypercare.
- Define delivery frameworks, SLAs, project milestones, resource capacity planning, and risk mitigation strategies to ensure predictable, on-time, and within-budget delivery.
- Own delivery commercials, engagement profitability, utilization metrics, and scope management across all active accounts.
- Establish and monitor quality benchmarks, coding standards, CI/CD/DataOps practices, and release management across teams.

Technical Leadership & Hands-on Architecture

- Serve as the principal SME and escalation architect for complex Databricks and Azure platform implementations.
- Lead architecture blueprints for enterprise Lakehouse implementations utilizing Medallion Architecture (Bronze/Silver/Gold), Delta Lake, Delta Live Tables (DLT), and Unity Catalog.




- Direct large-scale cloud migration strategies from legacy on-prem systems (e.g., Hadoop, Teradata, SQL Server) to Azure Databricks.
- Perform high-level code and architecture reviews, focusing on Spark distributed compute optimization, cluster tuning, I/O bottlenecks, and Azure cloud spend/finops governance.

Client Engagement & Strategic Account Growth

- Act as the trusted technical advisor and primary escalation point for client stakeholders.
- Collaborate with sales and client partners on pre-sales pursuits, high-level estimations, RFPs, technical defense, and statements of work (SOWs).
- Identify organic account expansion opportunities by recommending advanced data platform features, GenAI integration via Databricks Mosaic AI, and modern data governance.

Team Leadership, Hiring & Practice Development

- Manage, mentor, and scale a multi-tiered team of Data Architects, Tech Leads, and Data Engineers across onshore and offshore delivery models.
- Establish career pathways, skill development roadmaps, and competency-building programs around Azure Data Services and Databricks.
- Spearhead hiring by leading technical bar-raiser interviews and establishing rigorous evaluation standards.
- Drive strategic alliance initiatives and partner certifications with Microsoft and Databricks.





Required Qualifications & Experience

- Experience: 14+ years of total experience in IT/Software Engineering, with at least 8+ years focused in Data Engineering and 4+ years leading multi-project delivery teams or data practice groups.
- Databricks Ecosystem: Hands-on mastery of the Databricks Lakehouse Platform, including Apache Spark internals, PySpark, Delta Lake, Delta Live Tables (DLT), Unity Catalog, Databricks SQL, Databricks Workflows, and Lakeflow.
- Azure Cloud Data Stack: Deep practical experience with Azure Data Factory (ADF), ADLS Gen2, Microsoft Fabric, Azure Key Vault, Azure Event Hubs/IoT Hub, and Azure Monitor.
- Data Architecture & Modeling: Demonstrated track record architecting enterprise-scale analytical systems using Star Schema, Snowflake Schema, Data Vault 2.0, or Lakehouse dimensional modeling.
- DataOps & CI/CD: Hands-on experience designing robust CI/CD pipelines for data using Azure DevOps, GitHub Actions, Terraform/Bicep, and containerized deployment workflows.
- Programming: Advanced coding proficiency in Python/PySpark and complex ANSI SQL.
- Stakeholder & Delivery Management: Proven capability managing multiple external client engagements, steering committee presentations, and senior client expectations.

Preferred Certifications

- Databricks: Databricks Certified Solutions Architect Qualified / Databricks Certified Data Engineer Professional
- Microsoft Azure: Microsoft Certified: Azure Solutions Architect Expert / Azure Data Engineer Associate (DP-203)

📌 Director Data Engineering (Bengaluru)
🏢 Straive
📍 Bengaluru