Delivery Manager

About the Role

We are looking for an experienced Delivery Manager to lead our Data Engineering delivery portfolio. You will own end-to-end delivery of large-scale data programs for global clients, covering data platform modernization, cloud migration, pipelines, and analytics enablement. Overall 15+ yrs of experience -You will manage client relationships, delivery teams, financial performance, and quality outcomes. You will also help us grow the practice by bringing AI/ML and GenAI capabilities into engagements.

Key Responsibilities

Delivery Management

• Own delivery of multiple data engineering projects and programs across onshore/offshore models, ensuring on-time, on-budget, high-quality outcomes.
• Drive project governance: planning, risk and issue management, dependency tracking, change control, and escalation handling.
• Ensure adherence to SLAs, KPIs, and delivery best practices (Agile, DevOps, DataOps).
• Conduct regular delivery reviews, steering committee meetings, and status reporting with clients and internal leadership.

Client & Stakeholder Management

• Act as the primary delivery point of contact for senior client stakeholders (CIO, CDO, Heads of Data/Engineering).
• Build long-term client relationships, drive satisfaction (CSAT/NPS), and identify opportunities for account growth.
• Support pre-sales activities: solutioning, effort estimation, proposals, SOWs, and client presentations.

Technical Leadership & Solution Oversight

• Provide technical direction on data architecture, ETL/ELT pipelines, data lakes/lakehouses, data warehousing, and real-time streaming solutions.
• Guide teams on cloud data platform adoption (Azure, AWS, GCP) and modern data stack tools.
• Champion data quality, governance, security, and compliance standards.
• Identify opportunities to embed AI/ML, GenAI, and intelligent automation into data solutions.

People & Practice Management

• Lead, mentor, and grow a team of architects, leads, and data engineers (typically 40-100+ members).
• Manage resource planning, utilization, hiring, onboarding, and attrition.
• Build a culture of upskilling and certification in cloud, data, and AI technologies.
• Contribute to practice growth through accelerators, reusable frameworks, and thought leadership.

Financial & Operational Management

• Own project P&L, including revenue, margins, forecasting, billing, and cost optimization.
• Improve delivery efficiency using automation, productivity levers, and pyramid management.
• Ensure compliance with company processes, contractual obligations, and audit requirements.

Required Skills & Qualifications

• Bachelors or Master’s degree in Engineering, Computer Science, or a related field.
• 12-16 years of IT experience, with a strong background in data engineering/data warehousing and proven delivery management experience in an IT services or consulting environment.
• Track record of managing large, multi-million-dollar data programs with distributed teams.
• Hands-on understanding of:
• Cloud data platforms: Azure (Synapse, ADF, Databricks, Fabric), AWS (Redshift, Glue, EMR, S3), or GCP (BigQuery, Dataflow)
• Big data & processing: Spark, Kafka, Hadoop ecosystem, Snowflake, Databricks
• ETL/ELT & orchestration: Informatica, Talend, dbt, Airflow, or similar
• Data modeling, warehousing, lakehouse architecture, and data migration
• SQL, Python/Scala (for technical guidance and review)
• Strong experience with Agile/Scrum, SAFe, and DevOps/DataOps practices.
• Excellent command of project financials: estimation, budgeting, forecasting, and margin management.
• Strong communication, negotiation, and stakeholder management skills, with experience handling US/EU clients.
• PMP, PRINCE2, SAFe, or equivalent certification is preferred.

Good to Have (AI/ML Exposure)

• Experience delivering or overseeing AI/ML or GenAI projects (e.g., ML pipelines, MLOps, feature stores, RAG-based solutions, LLM integrations).
• Familiarity with tools such as Azure ML, SageMaker, Vertex AI, MLflow, or Databricks ML.
• Understanding of responsible AI, data privacy, and AI governance.
• Ability to position and sell AI-enabled data solutions to clients.
• Cloud or data certifications (Azure Data Engineer, AWS Data Analytics, Databricks, Snowflake, etc.).

Key Competencies

• Strategic and outcome-driven delivery mindset
• Strong leadership and people management
• Client-centric approach with an ownership attitude
• Problem-solving and crisis management
• Business acumen and commercial awareness
• Ability to balance technical depth with program-level oversight

What We Offer

• Opportunity to lead high-impact data and AI programs for global clients
• Competitive compensation and performance-linked incentives
• Continuous learning, certifications, and career growth into Practice Head / Delivery Head roles
• Collaborative, innovation-driven work culture