This role is for one of our clients
Industry: IT Services and IT Consulting

Seniority level: Mid-Senior level

Min Experience: 12+ years

Location: Bengaluru, Karnataka, India

JobType: full-time

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

We are looking for a Technical Project Manager who can drive end-to-end execution of complex Data Engineering, Analytics, and AI/ML projects. The role requires managing engineering execution, coordinating cross-functional teams, handling stakeholder communication, and ensuring timely delivery of scalable data and AI solutions. The idea candidate should understand technical architecture well enough to work directly with engineers, architects, and data scientists while keeping delivery on track.

Requirements
Key Responsibilities
Project Delivery & Execution Management

Own end-to-end delivery of complex technical projects from initiation to production deployment
Define project scope, timelines, milestones, deliverables, and execution strategy
Manage multiple concurrent technical projects with competing priorities
Ensure predictable delivery with strong governance around scope, timelines, quality, and execution
Drive project planning, sprint execution, release planning, and production readiness
Manage project risks, issue resolution, dependency tracking, and escalation management, financial metrics

Team Leadership, Mentoring & People Management

Proven experience managing and growing engineering teams of 10+ people - including hiring, performance management, and career development
Able to operate credibly in both technical design reviews and executive stakeholder meetings, switching registers fluently
Strong written and verbal communication: clear architecture decision records, concise board-level status updates, and structured client presentations
Conduct regular one-on-one discussions, coaching sessions, and career guidance
Drive team capability building and technical skill development initiatives
Foster accountability, ownership, collaboration, and engineering excellence culture
Support hiring, onboarding, and team expansion initiatives

Technical: Data Engineering

Deep, hands-on understanding of data engineering fundamentals: batch and streaming pipeline design, data modelling paradigms (dimensional, data vault, medallion architecture), and warehouse internals
Hands-on experience with cloud data warehouses - Databricks, Snowflake, BigQuery, AWS Redshift or Azure
Experience with data quality frameworks, lineage tooling, and metadata cataloguing at an enterprise level

Technical: AI & GenAI

Practical experience designing or overseeing production AI systems - RAG pipelines, LLM integrations, vector search, knowledge graphs, or agentic frameworks
Sufficient depth in LangChain, LangGraph, vector databases, and knowledge graph platforms (Neo4j) to lead architecture reviews, evaluate technical trade-offs, and guide engineering decisions
Ability to assess AI system designs for production readiness: latency, cost, observability, reliability, and governance compliance

Nice to Have

Experience contributing to pre-sales: RFP responses, solution architecture proposals, effort estimation, and POC delivery
Published technical writing, conference talks, or documented program case studies

Qualifications

10-12 years of experience in data and/or AI engineering, with the latter years in technical lead or project management roles
Demonstrated experience owning delivery of at least two large-scale, multi-workstream data or AI program from inception to production
Experience managing cross-functional engineering teams in a client-facing or consulting environment
Technical certifications in dbt, Snowflake, or a major cloud platform (Azure, AWS, GCP) are a strong plus

Must-have skills

technical project delivery, Data Engineering

Good-to-have skills

LLM, AWS

Technical Project Manager- Data Engineering/ Data Science/ AI & Gen AI