Role : Senior Technical Project Manager (Data / BI)

Company : R Systems

Location : Noida

Employment Type : Full-time

About the Role :

R Systems is looking for a Senior Technical Project Manager (Data / BI) to lead and drive enterprise-scale Data Engineering and Business Intelligence (BI) initiatives.

The ideal candidate will possess strong technical expertise in data platforms, analytics, cloud ecosystems, and BI solutions, combined with proven project management capabilities.

This role requires a professional who can bridge the gap between business stakeholders, engineering teams, and data-driven decision-making, while ensuring successful delivery of scalable data and BI programs.

Key Responsibilities :

Technical Project Management :

- Lead end-to-end delivery of Data Engineering and Business Intelligence (BI) projects across multiple business functions.

- Define project scope, timelines, milestones, risks, and delivery plans to ensure successful execution.

- Coordinate with internal stakeholders, engineering teams, product teams, and business leaders for seamless project delivery.

- Manage project governance, resource allocation, dependencies, and risk mitigation strategies.

Data Engineering & BI Leadership :

- Drive implementation and optimization of modern data platforms and BI solutions.

- Collaborate with engineering teams on data pipelines, ETL/ELT frameworks, data warehousing, and analytics architectures.

- Partner with BI teams to build scalable reporting and dashboarding solutions for business insights.

- Ensure data quality, governance, and reporting accuracy across systems.

AI-Driven Development & Productivity :

- Leverage AI-powered development tools such as Databricks AI Genie, Power BI Copilot, Cursor, or GitHub Copilot to improve delivery speed, development efficiency, and analytics productivity.

- Promote AI-assisted workflows and automation within project execution and technical delivery.

Cloud & Architecture Oversight :

- Work closely with teams deploying cloud-native data solutions on Azure, AWS, or GCP.

- Support architecture discussions for scalable and secure cloud-based analytics ecosystems.

- Ensure alignment with cloud best practices, security, and performance optimization.

Stakeholder Management & Collaboration :

- Translate business requirements into technical execution plans and actionable deliverables.

- Present project updates, technical recommendations, and delivery progress to leadership stakeholders.

- Foster collaboration across cross-functional teams to ensure business alignment and successful outcomes.

Continuous Improvement :

- Drive process optimization, project standardization, and best practices across data and BI initiatives.

- Stay updated with emerging technologies in data engineering, analytics, AI tooling, and cloud platforms.

Required Skills & Qualifications :

- 5 to 7 years of experience in Technical Project Management, Data Engineering, or BI-focused roles.

- Strong understanding of both Data Engineering and Business Intelligence (BI) ecosystems.

- Hands-on exposure to data platforms, analytics workflows, and reporting solutions.

- Experience with AI-powered developer/productivity tools such as :

1. Databricks AI Genie

2. Power BI Copilot

3. Cursor

4. GitHub Copilot

- Strong understanding of cloud ecosystems (Azure / AWS / GCP) for data and analytics solutions.

- Relevant Cloud Certifications (Azure, AWS, or GCP Data/Architect certifications) preferred.

- Excellent stakeholder management, communication, and project coordination skills.

- Strong analytical mindset with the ability to solve complex technical and business challenges.

Preferred Skills :

- Experience managing enterprise-scale Data, Analytics, or BI transformation projects.

- Familiarity with Agile / Scrum project delivery methodologies.

- Exposure to modern data stack, data lakes, warehousing, and visualization tools.

- PMP, Scrum, or cloud certifications would be an added advantage.

Why Join R Systems ?

- Opportunity to work on cutting-edge Data & BI transformation initiatives.

- Exposure to AI-enabled engineering and analytics ecosystems.

- Collaborative work environment with opportunities for career growth and innovation.

- Work alongside highly skilled teams building scalable enterprise solutions