Senior Data Product Manager

About The Role
We're looking for a senior
Data Product Manager
to drive the strategy, architecture, and execution of the data products that power Similarweb. This role is at the core of our data innovation engine, serving multiple business units and platform products across the company. You will lead cross-functional efforts to define, deliver, and scale data assets that are foundational to the Similarweb product and its market differentiation.

This role offers a unique opportunity to lead high-scale, high-impact data products by collaborating with R&D, product, and business stakeholders to architect modular, trusted, and intelligent data systems.

We're looking for a true data enthusiast: someone passionate about translating business needs into data solutions, building strong relationships, shaping methodologies and processes, and owning complex data initiatives from end to end.

This role will report to the VP of Product Management, Data.

What You'll Do
Data Product Ownership

• Own the vision, roadmap, and delivery of critical datasets that underpin platform functionality, decisioning systems, and customer-facing features.
• Lead modularization of data structures to enable scalability, easier ownership distribution, and data quality improvements.
• Introduce metrics for quality (completeness, coverage, freshness, accuracy) and define validation, logging, and governance frameworks.

Cross-Functional Leadership

• Serve as the product voice for data across R&D, aligning platform engineers, analysts, scientists, and business teams around a common strategy.
• Bridge between domain-specific product teams and platform data infrastructure, translating business needs into scalable, reusable data assets.
• Define data SLAs, fallback mechanisms, enrichment strategies, and quality assurance mechanisms in partnership with data consumers.

Strategic Impact

• Prioritize and plan data initiatives that support new verticals, geographies, product features, and business models.
• Spearhead productization of internal datasets into revenue-generating assets for both direct sales and platform distribution.
• Deeply understand the customer's evolving needs and enable the data to capture them accurately and scalably.

Execution & Optimization

• Write clear product specs that include technical definitions, mapping rules, edge case handling, and downstream consumption logic.
• Work hands-on with Databricks, Spark, SQL, and Python to analyze datasets, test logic, or collaborate on experiments.
• Identify data anomalies, misclassifications, and inconsistencies, and lead efforts to resolve them in systematic and productized ways.
• Design workflows for historical tracking and versioning of datasets.

Experience
What You Bring

• 4+ years of experience in data product management, or as a technical product manager or solutions architect in a big data environment.
• Proven track record in leading cross-functional data initiatives involving data engineering, data science, and analytics teams.
• Experience delivering data products for both revenue-generating direct sales use cases and scalable platform integration.
• Hands-on experience with large-scale data collection, classification, curation, and delivery systems, especially in companies that build or sell data products.
• Experience driving data modeling and transformation projects with complex entity relationships and high-quality standards.
• Practical exposure to AI/ML productization: partnering with data scientists to define training data, evaluate model performance, and integrate AI outputs into production systems.

Skills

• Strong analytical and systems-thinking mindset with deep understanding of how data flows and scales.
• Ability to define validation frameworks, QA rules, and performance metrics for structured and semi-structured data.
• Excellent communicator who can translate between technical and business stakeholders and align diverse interests into unified outcomes.
• Collaborative leadership style with a bias for action and ability to resolve ambiguity through structure and logic.

Technical Fluency

• Comfortable querying large datasets and working alongside large scale data pipelines.
• Familiarity with Python, Spark, Airflow, and cloud data environments (e.g., Databricks, S3, Snowflake) is a strong plus.
• Understanding of AI/ML lifecycle, including model inputs, inference pipelines, and continuous data feedback loops.

Why You'll Love Being a Similarwebber
You'll actually love the product you work with
: Our customers aren't our only raving fans. When we asked our employees why they chose to come work at Similarweb, 99% of them said "the product." Imagine how exciting your job is when you get to work with the most powerful digital intelligence platform in the world.

You'll find a home for your big ideas
: We encourage an open dialogue and empower employees to bring their ideas to the table. You'll find the resources you need to take initiative and create meaningful change within the organization.

We offer competitive perks & benefits:
We take your well-being seriously, and offer competitive compensation packages to all employees. We also put a strong emphasis on community, with regular team outings and happy hours.

You can grow your career in any direction you choose:
Interested in becoming a VP or want to transition into a different department? Whether it's Career Week, personalized coaching, or our ongoing learning solutions, you'll find all the tools and opportunities you need to develop your career right here.

Diversity isn't just a buzzword:
People want to work in a place where they can be themselves. We strive to create a workplace that is reflective of the communities we serve, where everyone is empowered to bring their full, authentic selves to work. We are committed to inclusivity across race, gender, ethnicity, culture, sexual orientation, age, religion, spirituality, identity and experience. We believe our culture of equality and mutual respect also helps us better understand and serve our customers in a world that is becoming more global, more diverse, and more digital every day.

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