Senior Technical Data Product Manager
M
MachinifyHealthcare Intelligence
Remote (United States)Full-TimeSenior
Salary180000 - 260000 USD per year
Apply NowOpens the employer's application page
Job Details
- Experience
- 10+ years total professional experience, 5+ years in product management roles
- Required Skills
- AWSPythonSQLAirflowPostgresSparkdbt
Requirements
- 10+ years total professional experience
- 5+ years in product management roles
- Prior hands-on experience as data engineer, data scientist, or analytics engineer
- Proven track record shipping data products or platforms used by internal/external teams
- Experience driving execution in matrixed organizations without direct authority
- Demonstrated ability to assess complex technical landscapes and define future-state architectures
- Data architecture expertise: data modeling, normalization/denormalization, distributed systems, batch/streaming patterns, ETL/ELT design
- Advanced SQL proficiency: complex queries, performance optimization, CDC patterns, data quality validation
- Cloud data infrastructure: AWS preferred (S3, Spark, RDS, DMS, Glue) or equivalent GCP/Azure experience
- Modern data stack fluency: data warehouses, lakehouse formats, orchestration tools (Airflow), transformation frameworks (DBT), BI platforms
- Analytical rigor: define metrics, analyze data, make data-driven decisions, identify patterns
- Strong stakeholder management across technical teams and business audiences
- Ability to translate complex technical architectures into business outcomes and vice versa
- Experience defining product vision, building roadmaps, and measuring success
- Proven influence without direct authority—building consensus through credibility and data-driven arguments
- Excellent written and verbal communication across all organizational levels
- Agile/Scrum methodology experience
Responsibilities
- Assess current state rapidly: Understand complex legacy landscapes, critical information, and system functionality
- Contribute to future state vision: Partner with VP Data Engineering, CTO, and architecture leads to shape target data architectures, canonical models, and platform capabilities
- Develop product roadmap: Translate business priorities into data product requirements, sequence initiatives, and balance migration work, new capabilities, and product enablement
- Support technical evaluations: Contribute product perspective to build vs. buy decisions, technology evaluations, and architectural choices
- Define and track success metrics: Establish product-level OKRs, track adoption, and communicate progress to stakeholders
- Drive cross-functional delivery: Coordinate data initiatives from requirements through production across various teams
- Unblock relentlessly: Identify and resolve dependencies, bottlenecks, and blockers
- Navigate complexity: Find critical information across legacy platforms and synthesize insights
- Facilitate decisions: Build consensus across teams with competing priorities
- Leverage AI extensively: Use LLMs and AI-powered tools to accelerate analysis, documentation, SQL generation, and decision-making
- Partner with technical leadership: Work closely with data engineering, data science, and architecture leads
- Translate requirements: Convert product team needs into clear technical requirements for engineering teams
- Enable product teams: Ensure downstream product teams can consume data platform capabilities through clear interfaces and documentation
- Participate in technical discussions: Engage substantively in reviews of ETL pipelines, data models, and distributed architectures
- Bridge stakeholders: Translate complex technical concepts into business value and bring business context to technical discussions
View Full Description & ApplyYou'll be redirected to the employer's site
