Pasig - Data Engineering Manager

As our Data Engineering Manager, you will lead and grow a team of Data Engineers embedded in various client accounts. You will be responsible for people development, performance management, delivery oversight, and organizational influence—working closely with our Head of Data Engineering and the Data Engineering Council.

You are expected to bring deep engineering experience to provide mentorship and coaching, challenge designs, and model sound engineering judgment—especially in solving ambiguous or poorly scoped problems, rather than writing code full-time.

Resposibilities:

• Manage and mentor a team of Data Engineers (mix of junior and senior)
• Conduct regular 1:1s, performance reviews, and career development planning
• Provide both mentorship and coaching to engineers at all levels
• Support onboarding and upskilling of Data Engineers across accounts

• Provide guidance on how Data Engineers design and develop data modeling, ETL/ELT pipeline architecture, testing, and documentation
• Provide development and standards for implementing the data engineering lifecycle and its undercurrents, such as Observability and Software Engineering for each Data Engineer
• Review technical work periodically (e.g., PRs, architecture proposals)
• Collaborate with senior engineers and the Data Engineering Council to set engineering standards and reuse strategies

• Partner with cross-functional leads (e.g., Data Visualization Engineers) to ensure smooth delivery across squads
• Monitor health of delivery: timelines, blockers, data quality issues
• Act as an escalation point for technical and operational challenges

• Help shape our technical onboarding, leveling framework, and Data Engineer career pathing
• Drive systems thinking: shared libraries, playbooks, reusable infra patterns
• Contribute to recruiting, hiring, and talent branding

Minimum Qualifications:

• 2+ years experience as a Senior-level Engineer, ideally in Data Engineering or a related software engineering domain
• Demonstrated ability to solve ambiguous or open-ended technical problems with minimal guidance
• Strong background in data modeling, with experience designing robust schemas for analytics or operational workflows
• More than 1 year in a people leadership role (official title or demonstrated experience)
• Experience providing both mentorship and coaching
• Strong grasp of modern data stacks: DBT, Airflow, Snowflake/BigQuery, Python, etc.
• Has a firm foundation in a cloud service provider, such as AWS
• Experience working in client-facing, services, or consulting environments
• Excellent communication skills: can coach junior engineers and discuss strategy with executives

Having the following is an advantage:

• Experience managing distributed teams or remote-first orgs
• Exposure to data visualization workflows, BI toolchains, and/or data science systems
• Familiarity with agile delivery, sprint rituals, and async documentation
• Prior involvement in building internal data tooling or enablement platforms