Delivery Director, Data Platforms and Engineering - Hybrid

We currently have a career opportunity for a Delivery Director to join our Data and Analytics team! This is a hybrid role that can be located near any of our 23 offices nationally.

The Director of Data Platforms & Engineering is a strategic consulting leader responsible for shaping and delivering transformative data platform and integration solutions for clients across industries. This role drives the vision, architecture, and execution of modern data ecosystems, leveraging technologies such as Databricks, Snowflake, dbt, Fivetran, and Informatica. Leading global teams of engineers and solution architects, the Director partners closely with clients to understand business objectives, design scalable and secure data strategies, and ensure successful implementation through hands-on leadership and thought partnership.

Our Data & Analytics team drives cutting-edge innovation in digital transformation deployment globally and across industries. We partner with a diverse range of clients and support them at every stage of the data lifecycle—from curation and ingestion to management, analytics, and reporting. Our practice spans AI, Data Management, Content, Data Strategy, and more. From building modern data platforms to applying machine learning and generative AI, we help organizations unlock deeper insights, automate decision-making, and drive smarter outcomes. In our collaborative, fast-paced environment, you’ll work with industry-leading tools and technologies, tackling real-world challenges and delivering impactful solutions that shape the future of digital transformation. 

 

Strategic Leadership

• Lead the development of strategic roadmaps and offerings for data platform practice.
• Define and execute the global data engineering strategy aligned with business goals and initiatives.
• Oversee the design, implementation, and management of offerings for enterprise data platforms (data lakes, warehouses, lakehouse, data mesh, real-time streaming) for customers.
• Evaluate emerging technologies and recommend adoption to enhance enterprise capabilities.

Team & Talent Management

• Build, mentor, and scale high-performing global teams of data engineers, architects, and integration specialists.
• Foster a culture of collaboration, innovation, accountability, and continuous learning.
• Attract and retain top talent.
• Drive career development, performance management, and succession planning.
• Experience leading Global teams and managing multiple managers

Client & Project Leadership (Consulting Focus)

• Serve as a trusted advisor to C-level clients, translating business needs into technical solutions.
• Lead multimillion-dollar engagements, including scoping, pricing, and delivery oversight.
• Manage vendor relationships and software partnerships to ensure best-in-class tooling and support.
• Collaborate with CIOs and executive sponsors to communicate strategy, performance, and ROI.

Technical Execution

• Architect scalable, high-performance, and cost-effective data solutions.
• Lead architecture reviews, design sessions, and technical governance.
• Champion DevOps/DataOps practices including CI/CD, IaC, and automated testing.
• Ensure compliance with data privacy regulations (e.g., GDPR, CCPA).
• Implement best practices and standards across business lines for consistency and scalability.

Thought Leadership & Innovation

• Stay abreast of industry trends and emerging technologies in data engineering and AI.
• Contribute to thought leadership through whitepapers, blogs, and presentations.
• Promote the firm’s expertise at industry events, conferences, and forums.

Pre-Sales & Go-To-Market Support

• Collaborate with sales and marketing teams to develop tailored proposals and go-to-market strategies.
• Conduct client presentations to articulate the value of data platform and AI/ML/Gen AI services.
• Create targeted collateral and case studies showcasing data and AI capabilities.

Required

• 15+ years in data engineering or integration roles, with 7+ years in senior leadership.
• Proven experience managing large, distributed teams and enterprise-scale data platforms.
• Deep expertise in cloud-native architectures (Databricks, Snowflake, Informatica, dbt, Fivetran, Kafka, Airflow).
• Strong understanding of data modeling, data warehousing, and data governance.

Preferred

• Experience in consulting or professional services environments.
• Experience with AI/ML integration, LLMs, and real