Data Technical Project Manager

Job Summary

We are looking for a Technical Project Manager with expertise in agile delivery and strong knowledge of data platforms and cloud engineering to oversee development and deployment cycles within StarHub’s Customer 360 (C360) data domains. The role requires close collaboration with Domain Owners, Data Architects, Engineering Managers, Platform Engineers, and Business Data Analysts/Scientists to ensure timely and quality delivery supporting analytics, artificial intelligence, and machine learning initiatives.

Key Responsibilities

• Lead agile ceremonies including sprint planning, daily stand-ups, and retrospectives to sustain team momentum and rhythm.
• Maintain backlog quality by refining, estimating, and prioritizing user stories.
• Plan and manage phased deployments across DEV, SIT, and PROD environments leveraging AWS and Snowflake platforms.
• Monitor delivery metrics such as team velocity, throughput, data quality SLAs, and pipeline stability.
• Proactively identify and resolve blockers, risks, and inter-domain dependencies.
• Create and maintain transparent delivery dashboards and status reports for senior stakeholders.
• Ensure alignment among Data Engineering, DevOps, and AI/ML teams for a cohesive delivery process.
• Collaborate closely with Domain Owners, Data Source Owners, Data Architects, and Engineers to align deliverables to critical data and analytics milestones.
• Coordinate with DevOps and QA/QE teams to confirm readiness for integration, testing, and release activities.
• Manage delivery dependencies with external partners involved in data ingestion, migration, and machine learning projects.
• Support Domain Owners by reporting DataOps KPIs such as ingestion success rates, pipeline failure rates, data freshness, and platform cost utilization.
• Participate in sprint demonstrations to validate that acceptance criteria are fulfilled.
• Engage with Data Owners, Business Unit Data Leads (across CBG, EBG, FIN, COPS, SmartHub), and Release Program Managers to synchronize sprint deliverables with broader project milestones.
• Work alongside Journey Owners and stakeholders to clarify priorities and expected delivery outcomes.
• Communicate risks, decisions, and delivery trade-offs effectively across stakeholders.
• Promote adoption of agile methodologies, DataOps, MLOps, and cloud automation best practices within the DXP Data teams.
• Analyze operational and delivery metrics to find opportunities for improvements in throughput, cost efficiency, and data quality.
• Support incident root cause analyses and post-mortem reviews to ensure lessons learned are integrated into backlogs.
• Contribute to standardized governance, templates, and documentation to unify delivery practices across domains.
• Advocate cost monitoring and optimization frameworks for Snowflake warehouses, AWS consumption, and data pipeline efficiency.

Requirements & Qualifications

• Bachelor’s degree in Data Science, Information Systems, Business Analytics, or a related discipline.
• Certifications in Agile (CSM, SAFe), PMP, DevOps, AWS Solutions Architect, or SnowPro Core are preferred.
• At least 8 years of experience in data platform delivery, DataOps and data quality management, or analytics program management.
• A minimum of 3 years in technical project management, delivery lead, or scrum master roles.
• Proven success managing data engineering teams that deliver pipelines and analytics through CI/CD in AWS and Snowflake ecosystems.
• Experience in coordinating data ingestion, modeling, and machine learning engineering leveraging modern tools such as Snowflake, Apache Airflow, Airbyte, NiFi, and AWS SageMaker.
• Strong grasp of DataOps automation, role-based access controls, data security, and cost efficiency in cloud data environments.
• Familiarity with tools such as Jira, Confluence, GitLab, Jenkins, Monday.com, Snowflake, SQL, and dashboard solutions.
• Industry experience in telecommunications, data platform delivery, or enterprise analytics programs is advantageous.

Skills

• In-depth knowledge of agile data engineering practices and cloud architecture.
• Proficiency with DevOps methodologies and related tooling.
• Competence in fostering a data-driven culture and enhancing data literacy across teams.
• Ability to distill complex technical details into clear, actionable plans.
• Strong communication, facilitation, and stakeholder management capabilities.
• Analytical, detail-oriented mindset focused on execution and continuous improvement.
• Highly organized, proactive, and adaptable in fast-paced environments.
• Commitment to operational excellence and process enhancements.