Note: The job is a remote job and is open to candidates in USA. gWorks builds software that helps small local governments work better. As a Technical Program Manager for Data Engineering, you’ll coordinate complex data initiatives, collaborating with various stakeholders to ensure projects are executed efficiently and effectively.
Responsibilities
- Own the planning, execution, and delivery of data engineering projects, including pipeline development, schema migrations, platform integrations, and data quality initiatives
- Define and maintain project plans, milestones, and dependencies in Jira, ensuring work is accurately tracked and consistently reflected across epics, stories, and sprints
- Lead sprint ceremonies — planning, standup, review, and retrospective — for data engineering teams, facilitating discussions and driving toward actionable outcomes
- Proactively identify blockers, surface trade-offs, and escalate risks before they become delivery problems
- Manage project scope and change requests with discipline, maintaining alignment between technical execution and business intent
- Serve as the primary coordination layer between data engineering and the engineering, analytics, product, and operations teams that depend on its outputs
- Translate business requirements from non-technical stakeholders into well-scoped technical work, and communicate technical decisions and trade-offs back in terms stakeholders can act on
- Build and maintain lightweight RACI structures and communication norms across projects to reduce ambiguity and keep everyone aligned
- Facilitate cross-team prioritization conversations, especially where data deliverables are on the critical path of a larger product or engineering initiative
- Design and maintain team and project metrics reports using Jira, covering velocity, throughput, cycle time, sprint completion rates, and SLA adherence for data pipelines
- Build and own recurring reporting cadences — weekly status updates, executive dashboards, and quarterly program reviews — that give leadership clear, accurate visibility into data engineering health and progress
- Partner with data engineers to instrument pipeline monitoring and tie operational health metrics into project-level reporting
- Use metrics to identify systemic inefficiencies, recurring blockers, or estimation drift, and bring data-driven recommendations to planning
- Own and continuously improve the team’s ways of working — Jira hygiene standards, sprint norms, documentation practices, and intake processes for new project requests
- Develop and maintain internal playbooks for common project types (e.g., new pipeline builds, data migrations, client onboarding workflows) to reduce ramp time and increase consistency
- Help the data engineering team operate with more autonomy by reducing process overhead, improving tooling, and keeping noise away from technical work
Skills
- 5+ years of experience in technical program management, with direct ownership of software or data engineering programs
- Deep, hands-on proficiency with Jira — including advanced board configuration, JQL, custom fields, workflow automation, and building reports and dashboards using built-in tools or Jira's reporting APIs
- Demonstrated experience building and owning project and team metrics programs — not just tracking tasks, but designing reporting frameworks that drive decisions
- Sufficient technical depth in data engineering to hold substantive conversations with engineers about pipeline architecture, orchestration, data quality, and schema design — and to understand the implications of technical decisions on project timelines
- Proven track record of coordinating complex, cross-functional projects across engineering, product, analytics, and business stakeholders
- Strong written and verbal communication skills — you write clear status updates, facilitate productive meetings, and adapt your communication style for technical and non-technical audiences
- Experience with agile methodologies (Scrum, Kanban, or hybrid), including running ceremonies and continuously improving team process
- Comfort with ambiguity and a bias toward action — you drive clarity rather than waiting for it
- Hands-on experience with AWS data services (Step Functions, Glue, S3, Athena, Lambda) at a conceptual or operational level
- Familiarity with data lakehouse concepts, medallion architecture, or data quality frameworks (Great Expectations, Soda)
- Experience working in a GovTech, SaaS, or data-platform company
- Exposure to Confluence, Notion, or similar tools for managing team documentation alongside Jira
- Experience with data observability or pipeline monitoring tools (Monte Carlo, Datafold, or similar)
Benefits
- Full medical, dental, and vision insurance
- 401(k) with company match
- PTO and paid holidays
- A collaborative team culture that values autonomy, growth, and execution
Company Overview
Company H1B Sponsorship