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SAVP - Director of Data Engineering

Job Description - SAVP - Director of Data Engineering

Description

Director of Data Engineering / Delivery Manager


Experience


15+ Years


Location


Flexible / Hybrid


Role Summary


We are seeking an experienced Director of Data Engineering / Delivery Manager to lead large-scale data and analytics programs, drive engineering excellence, and manage delivery across multiple strategic accounts. The ideal candidate will have deep expertise in modern data platforms, cloud technologies, data engineering, stakeholder management, and team leadership.


This role requires ownership of end-to-end delivery, engineering governance, client relationship management, account growth, and building high-performing data engineering teams. 



Responsibilities

Delivery Leadership



  • Own end-to-end delivery of enterprise data engineering and analytics programs.

  • Ensure projects are delivered on time, within budget, and with high quality.

  • Establish delivery governance, risk management, and execution frameworks.

  • Lead multi-workstream programs involving data platforms, cloud modernization, AI/ML, and analytics initiatives.

  • Drive delivery excellence through Agile and DevOps best practices. 


Data Engineering & Technology Strategy



  • Define and execute enterprise data platform roadmaps.

  • Lead architecture decisions across Azure, AWS, GCP, Snowflake, Databricks, Microsoft Fabric, and modern data ecosystems.

  • Drive adoption of scalable data architectures including Lakehouse, Data Mesh, and Data Products.

  • Ensure data quality, governance, security, and compliance standards.

  • Champion innovation in AI, Generative AI, and advanced analytics platforms. 


Stakeholder & Client Management



  • Serve as a trusted advisor to senior client executives.

  • Lead executive steering committee meetings and governance reviews.

  • Manage escalations and ensure stakeholder satisfaction.

  • Drive strategic account growth through identification of new opportunities.

  • Collaborate with business, architecture, security, and product teams. 


People Leadership



  • Build, mentor, and scale high-performing data engineering teams.

  • Manage Engineering Managers, Architects, Leads, and Data Engineers.

  • Drive workforce planning, hiring, succession planning, and capability development.

  • Foster a culture of innovation, accountability, and continuous learning.

  • Lead onshore and offshore delivery teams. 


Financial & Operational Management



  • Own program budgets, forecasting, revenue, and margin targets.

  • Optimize resource utilization and delivery efficiency.

  • Monitor KPIs covering delivery health, engineering productivity, quality, and customer satisfaction.


Support proposal development, solutioning, estimations, and RFP responses. 



Qualifications

Data Engineering



  • Enterprise Data Platforms

  • Data Warehousing & Lakehouse Architectures

  • ETL/ELT Frameworks

  • Data Modeling (Star, Snowflake, Dimensional)

  • Streaming & Real-Time Processing

  • Data Governance & Metadata Management


Cloud & Platform Technologies



  • Azure (ADF, ADLS, Synapse, Fabric)

  • AWS

  • GCP

  • Databricks

  • Snowflake

  • Microsoft Fabric


Programming & Engineering



  • Python

  • SQL

  • Spark / PySpark

  • Scala (preferred)

  • CI/CD

  • Azure DevOps

  • GitHub

  • Terraform


Leadership & Delivery



  • Agile Program Delivery

  • Account Management

  • Executive Stakeholder Management

  • Delivery Governance

  • Team Building & Mentoring

  • Strategic Planning


Qualifications



  • Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or related field.

  • 15+ years of progressive experience in Data Engineering, Analytics, and Technology Delivery.

  • 5+ years leading enterprise-scale data programs and engineering teams.

  • Experience managing large global delivery teams and strategic client engagements.

  • Cloud certifications (Azure, Databricks, Snowflake, Fabric, AWS) preferred.


Success Metrics



  • Delivery SLA adherence

  • Revenue & Margin Achievement

  • Customer Satisfaction (CSAT)

  • Team Utilization & Retention

  • Platform Modernization Outcomes

  • Quality & Defect Metrics

  • Innovation and Automation Adoption


Account Growth & Expansion



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