Data Technical Project Manager (TPM)

Job Description

We are seeking a Technical Project Manager who can combine agile delivery discipline with data platform and cloud engineering literacy to coordinate development and release cycles across StarHub’s C360 data domains.

In this role, you will work closely with Domain Owners (DOs), Data Architects, Engineering Managers (EMs), Platform Engineers, and Biz Data Analysts/Scientists to ensure on-time, high-quality delivery across systems that support StarHub’s analytics, AI, and machine learning journeys.

The ideal candidate will have strong hands-on experience with agile project delivery in a DataOps or cloud-native environment, preferably across data ingestion, transformation, and machine learning pipelines - with a solid understanding of Snowflake, AWS, CI/CD, MLOps and observability frameworks, and end-to-end delivery metrics.

Key Responsibilities

Delivery & Agile Management

• Drive agile ceremonies (sprint planning, stand-ups, retrospectives) and maintain team rhythm and cadence.
• Manage backlog hygiene, ensuring stories are well-defined, estimated, and prioritized.
• Plan and execute phased delivery strategies across multiple environments (DEV/SIT/PROD) within AWS and Snowflake ecosystems.
• Track delivery health through velocity, throughput, data quality SLAs, and pipeline stability metrics.
• Identify and resolve blockers, risks, and cross-domain dependencies early.
• Maintain clear delivery dashboards and status reporting to senior stakeholders.
• Ensure alignment between Data Engineering, Platform DevOps, and Analytics/ML teams for synchronized delivery.

Technical Coordination & Planning

• Partner with Domain Owners, Data Source Owners, Data Architects & Engineers to align deliverables to data and analytics milestones.
• Coordinate with DevOps and QA/QE teams to ensure readiness for integration, testing, and release.
• Coordinate delivery dependencies with external partners across ingestion, migration, and ML projects.
• Support Domain Owners and report on key DataOps KPIs, including ingestion success rate, pipeline failure rate, data freshness, and platform cost utilization..
• Participate in sprint demos and ensure acceptance criteria are met for each increment.

Stakeholder & Cross-Domain Collaboration

• Work with Data Owners, Business Unit Data Leads (CBG, EBG, FIN, COPS, SmartHub), and Release Program Managers to align sprint deliverables to journey-level milestones.
• Collaborate with Journey Owners (JOs) and business stakeholders to clarify priorities and expected outcomes.
• Coordinate delivery dependencies with external partners across ingestion, migration, and ML projects.
• Communicate risks, decisions, and delivery trade-offs clearly across key stakeholders.

Continuous Improvement & Governance

• Drive adoption of agile, DataOps, MLOps and cloud automation best practices across DXP Data teams.
• Analyze delivery and operational metrics to identify improvement opportunities in throughput, cost efficiency, and data quality.
• Support incident RCA reviews and platform post-mortems, ensuring learnings are captured and converted into actionable backlog improvements.
• Contribute to standardized delivery governance, templates, and documentation across domains.
• Champion cost optimization and monitoring frameworks for Snowflake warehouses, AWS usage, and data pipeline efficiency.

Qualifications

Education & Certifications

• Bachelor’s degree in data science, Information Systems, Business Analytics or related field.
• Agile, PMP, or DevOps certifications (e.g., CSM, SAFe, PMI-ACP, AWS Certified Solutions Architect, SnowPro Core) preferred.

Experience

• 8+ years of experience in data platform delivery, data ops & quality management, or analytics program management, with at least 3 years in a technical project management, delivery lead or scrum master capacity.
• Proven track record managing data engineering teams delivering pipelines and analytics workloads via CI/CD within AWS and Snowflake architectures..
• Proven experience coordinating ingestion, modeling, and ML engineering deliveries based on modern data tech stacks such as Snowflake, Apache Airflow, Airbyte, NiFi and AWS SageMaker.
• Strong understanding of DataOps automation, role-based access control, data security, and cost optimization in cloud data environments..
• Hands-on level familiarity with tools such as Jira, Confluence, GitLab, Jenkins, Monday.com, Snowflake, SQL, dashboarding.
• Experience in telecommunications, data platform delivery, or enterprise analytics programs is an advantage.

Skills

• Deep understanding of agile data engineering, cloud architecture, and DevOps principles.
• Demonstrated experience fostering data-driven culture and enabling data literacy across cross-functional teams.
• Ability to translate technical complexity into clear, actionable plans.
• Exceptional communication, facilitation, and stakeholder management skills.
• Analytical and detail-oriented mindset with a bias for execution.
• Highly organized, proactive, and resilient in a dynamic, fast-paced environment.
• Passion for continuous improvement and operational excellence.