Data Engineering & AI Practice Lead

About ThoughtFocus ThoughtFocus is a global IT services and solutions company with deep capabilities across Data & Analytics, Cloud, Modern Engineering, and Financial Services technology. Headquartered in the US with delivery centers in India, we partner with leading enterprises to build scalable, future-ready technology solutions. Our teams are built on a culture of ownership, expertise, and long-term client partnerships and talent is at the heart of how we grow. - https://thoughtfocus.com/ About the Role The Data Engineering & AI Practice Lead owns the end-to-end health of the Data Engineering and AI practice within our IT services business. This is a hybrid leadership role that combines technical depth with client-facing gravitas you will shape the practices offerings, win new business in presales, architect solutions during solutioning, and drive delivery excellence across active engagements. You will act as the go-to authority for all things data and AI inside the firm, bridging the gap between what clients need and what our engineering teams deliver. Key Responsibilities 1. Presales & Business Development Collaborate with Sales and Account Management teams to qualify and pursue data & AI opportunities. Lead client discovery workshops to uncover pain points, assess data maturity, and identify high-value AI use cases. Author and present compelling proposals, RFP responses, and capability decks tailored to each prospects business context. Define competitive pricing models, effort estimates, and engagement constructs (T&M, fixed-price, outcome-based). Build and maintain a reusable presales asset library: solution blueprints, case studies, demo environments, and ROI calculators. Represent the practice at industry conferences, webinars, and client briefings to establish thought leadership. 2. Solutioning & Architecture Lead architecture design for data platform, AI/ML, and analytics engagements from conceptual to detailed solution design. Define reference architectures across modern data stack components: ingestion, lakehouse/ warehouse, orchestration, serving, and AI/ML pipelines. Evaluate and recommend technology choices (e.g., Databricks, Snowflake, dbt, Apache Spark, Azure/AWS/GCP native services, LLM frameworks). Produce high-quality SOWs, architecture decision records (ADRs), and solution design documents. Drive POC/prototype builds to validate technical feasibility and de-risk client commitments. Stay current on emerging trends (GenAI, LLMOps, real-time streaming, data mesh, data contracts) and translate them into practice offerings. 3. Delivery Excellence Establish and govern delivery standards, engineering best practices, and quality gates across active data & AI projects. Define and enforce CI/CD, testing, data quality, observability, and documentation standards for the practice. Conduct milestone reviews and architecture governance checkpoints to identify risks early. Serve as executive escalation point for critical delivery issues; provide hands-on guidance to project teams. Build and own the practices capability roadmap: identify skill gaps, drive training, and recruit senior talent. Track practice-level KPIs (utilization, CSAT, delivery quality, reuse index) and report to leadership. 4. Practice Building & Thought Leadership Define and maintain the practices service catalog, go-to-market positioning, and tiered offering structure. Create and evangelize accelerators, frameworks, and IP assets that reduce time-to-value for clients. Mentor architects and senior engineers; run internal CoPs (Communities of Practice) for data engineering and AI. Partner with technology alliance teams (Databricks, Snowflake, AWS, Azure, Google) to deepen partnerships and co-sell. Qualifications Required 15+ years of hands-on experience in data engineering, analytics, or AI/ML with at least 3 years in a practice lead, principal architect, or senior manager capacity at an IT services or consulting firm. Deep expertise in modern data platforms: lakehouses (Databricks, Apache Iceberg), cloud data warehouses (Snowflake, BigQuery, Redshift), and orchestration (Airflow, dbt, Prefect). Proven track record of winning and delivering data/AI engagements worth $500K$5M+. .