Delivery Head

We are an AI-led, platform-driven Digital Engineering and Enterprise Modernization partner, combining deep technical expertise and industry experience to help our clients anticipate what’s next. Our offerings and proven solutions create a unique competitive advantage for our clients by giving them the power to see beyond and rise above. We work with many industry-leading organizations across the world, including 20 Fortune 50 companies and 4 of the 5 top banks in both the US and India, and numerous innovators across the healthcare ecosystem.

Our disruptor’s mindset, commitment to client success, and agility to thrive in the dynamic environment have enabled us to sustain our growth momentum. Persistent has been recognized across top industry platforms for innovation, leadership, and inclusion. We have delivered 23 sequential quarters of growth with $422.5M in Q3 FY26 revenue, up 4.0% Q-o-Q and 17.3% Y-o-Y growth. Our 26,500+ global team members, located in 18 countries, have been instrumental in helping the market leaders transform their industries. We won the 2025 ISG Star of Excellence™ Award for AI and Data Excellence and were named a Leader in the Everest Group Talent Readiness for Next-generation Data, Analytics and AI Services PEAK Matrix® Assessment 2025.

Our company fosters a values-driven and people-centric work environment that enables our employees to:

• Accelerate growth, both professionally and personally
• Impact the world in powerful, positive ways, using the latest technologies
• Enjoy collaborative innovation, with diversity and work-life wellbeing at the core
• Unlock global opportunities to work and learn with the industry’s best

Position: Delivery Head - Data & Analytics

Location: Bay Area or Dallas

Industry / Domain: Data & Analytics / Hi-Tech

Role Overview

We are seeking an accomplished Delivery Head to lead data engineering delivery across a portfolio of Hi-Tech customers — including semiconductor, hardware, SaaS, platform, Hyperscalers and consulting companies. This is a senior, client-facing leadership role accountable for the end-to-end health of multiple concurrent engagements: delivery quality, financial performance (revenue and margin), talent, and long‑term client relationships.

The ideal candidate blends deep, hands‑on data engineering credibility with the executive presence to operate as a trusted advisor to client CXOs and internal leadership. You will scale delivery teams, institutionalize engineering best practices, and drive measurable business outcomes for customers operating at the leading edge of technology.

Key Responsibilities

Delivery & Program Leadership

• Own end-to-end delivery across a portfolio of data engineering engagements, ensuring on-time, on-budget, and high-quality outcomes against agreed SLAs and OKRs.
• Establish delivery governance — cadences, dashboards, risk/issue management, and escalation paths — across multiple programs and distributed (onshore/offshore) teams.
• Drive engineering excellence in data platform modernization, pipeline development, data quality, and DataOps across cloud environments.
• Serve as the senior delivery point of contact for Hi-Tech clients, building durable, trust-based relationships with client stakeholders up to CXO level.
• Partner with sales and account teams to grow existing accounts — identifying opportunities, shaping solutions, and supporting proposals, estimations, and SOWs.
• Translate client business challenges into data engineering roadmaps that deliver tangible value (time‑to‑insight, cost optimization, data reliability).

Organic Growth, Financial & Commercial Ownership

• Drive organic growth within existing accounts — accountable for account‑level revenue and margin targets, farming and expansion of the portfolio, and identifying and converting new opportunities.
• Own revenue and gross‑margin targets for the portfolio; manage forecasting, resource planning, utilization, and profitability.
• Optimize delivery models and pyramids to improve margins without compromising quality or client satisfaction.

Practice & Capability Building

• Contribute to the data engineering practice — reusable accelerators, reference architectures, delivery playbooks, and points of view tailored to Hi-Tech use cases.
• Stay current with the evolving data ecosystem and guide adoption of emerging tools, patterns, and (where relevant) GenAI-enabled data workflows.

Required Qualifications & Experience

• 12–15 years of overall IT experience, with a strong foundation in data engineering, data warehousing, or data platform development.
• 4+ years in a delivery, program, or engagement leadership role owning multiple concurrent projects or a portfolio.
• Demonstrated P&L or financial ownership — managing revenue, margin, forecasting, and staffing
• Experience managing distributed onshore/offshore delivery teams.

Technical Depth

Hands‑on credibility across the modern data engineering stack is essential, even though the role is leadership-oriented.

Must have

• Must have implemented cloud data platforms end‑to‑end (design through production), not only overseen them.
• Strong, hands‑on familiarity with Databricks and Snowflake.

Broader stack

• Data processing & orchestration: Spark, Airflow, dbt, Kafka.
• Data warehousing / lakehouse: Delta Lake and equivalent patterns.
• Pipeline & integration: ETL/ELT design, streaming and batch, CDC.
• DataOps, data quality, governance, lineage, and observability practices.
• Executive presence and communication — credible with both engineering teams and client executives.
• Stakeholder management, negotiation, and conflict resolution.
• Ability to lead through ambiguity and scale teams in a fast‑moving environment.

Preferred / Nice-to-Have

• Relevant cloud or platform certifications (AWS/Azure/GCP, Databricks, Snowflake).
• Exposure to GenAI / ML data pipelines and feature/vector stores.
• Experience with pre‑sales, solutioning, and RFP responses in a services context.
• Familiarity with Hi-Tech domain data (supply chain, telemetry/IoT, product usage, chip design workflows).

Education

Bachelor’s or Master’s degree in Computer Science, Engineering, Information Technology, or a related field.