Director Product Manager Data Orchestration and Insights

Workato transforms technology complexity into business opportunity. As the leader in enterprise orchestration Workato helps businesses globally streamline operations by connecting data processes applications and experiences. Its AIpowered platform enables teams to navigate complex workflows in realtime driving efficiency and agility.

Trusted by a community of 400000 global customers Workato empowers organizations of every size to unlock new value and lead in todays fastchanging world. Learn how Workato helps businesses of all sizes achieve more atworkato.

Ultimately Workato believes in fostering aflexible trustoriented culture that empowers everyone to take full ownership of their roles. We are driven byinnovationand looking forteam playerswho want to actively build our company.

But we also believe inbalancing productivity with selfcare. Thats why we offer all of our employees a vibrant and dynamic work environmentalong with a multitude of benefitsthey can enjoy inside and outside of their work lives.

If this sounds right up your alley please submit an application. We look forward to getting to know you!

Also feel free to check out why:

• Business Insidernamed us an enterprise startup to bet your career on

• Forbes Cloud 100recognized us as one of the top 100 private cloud companies in the world

• Deloitte Tech Fast 500ranked us as the 17th fastest growing tech company in the Bay Area and 96th in North America

• Quartzranked us the #1 best company for remote workers

As Director Product Manager you will define and execute the strategy to establish Workato as the enterprise leader in data orchestration. Your goal is to build aunified platformthat seamlessly orchestrates data pipelines forETL ELT and Reverse ETL (data activation)eliminating the need for fragmented tools and enabling enterprises to move data efficiently across their ecosystem.

• Develop and execute the product strategy for a unified data orchestration platform supporting ETL ELT and Reverse ETL (data activation) across SaaS data warehouses data lakes and custom sources.
• Define and prioritize builtin transformation capabilities and integrations with tools like DBT and Coalesce to scale ELT pipelines efficiently.
• Ensure seamless data ingestion movement and activation across structured semistructured and unstructured data formats.

• Embed data quality lineage governance and operational analytics as core platform features ensuring enterprises have builtin compliance and data integrity controls.
• Develop native observability and automation tools to monitor pipeline performance detect anomalies and proactively enforce data governance policies.
• Ensure the platform meets enterprise security compliance and scalability requirements making Workato the goto orchestration solution for largescale deployments.

• Leverage AI to enhance data classification transformation recommendations and selfhealing pipelines that minimize operational overhead.
• Integrate predictive analytics and semantic enrichment to automate data mapping improve pipeline efficiency and surface actionable insights.
• Work with AI research teams to infuse machine learning into Workatos data services driving continuous optimization and smarter decisionmaking.

• Architect a selfservice data virtualization platform that provides a self service experience enabling users to explore and analyze data from thirdparty apps data warehouses data lakes Workato usage data and custom datasets in real time.
• Develop interactive dashboards and AIpowered analytics that empower businesses to make datadriven decisions without deep technical expertise.
• Ensure seamless crossplatform data integration to unify enterprise data landscapes and drive deeper insights.

• Collaborate with engineering UX and gotomarket teams to ensure seamless feature adoption.
• Act as a thought leader internally and externally driving customer trust and enterprise adoption.

• 7 years of product management experience in SaaS or B2B environments specializing in data management data orchestration or infrastructure products.
• Proven success in shipping and scaling complex data products with measurable business impact.
• Strong track record in leading crossfunctional teams influencing product strategy and driving in fastpaced environments.

• Deep expertise in ETL ELT Reverse ETL and data activation pipelines.
• Strong understanding of modern data architecture including data lakes data warehouses structured and semistructured data processing.
• Experience with data transformation tools (DBT Coalesce) and orchestration frameworks (Airflow Dagster) to build scalable pipelines.
• Knowledge of realtime data movement databases (Oracle SQL Server PostgreSQL) and cloud analytics platforms (Snowflake Databricks BigQuery).
• Familiarity with emerging data technologies like Open Table Format Apache Iceberg and their impact on enterprise data strategies.
• Handson experience with data virtualization and analytics platforms (Denodo Domo) to enable seamless selfservice data exploration and analytics.
• Strong background in cloud platforms (AWS Azure Google Cloud) and their data ecosystems.

• Experience integrating AI/MLdriven insights into data management products to enhance data quality lineage tracking and transformation recommendations.
• Strong understanding of predictive analytics anomaly detection and semantic data enrichment for operational intelligence.

• Deep knowledge of data security compliance and governance best practices for enterprise data platforms.
• Experience embedding data lineage tracking data quality validation and operational analytics as core product functionalities.
• Strong expertise in realtime observability automation and performance monitoring for data pipelines.

• Ability to deeply understand customer needs across data engineering analytics and business intelligence teams.
• Proven ability to translate complex technical concepts into intuitive userfriendly product capabilities.
• Skilled at collaborating with engineering UX security legal and gotomarket teams to drive enterprise adoption.

• Strong ability to use customer research data analytics and competitive insights to inform product decisions.
• Experience analyzing largescale data platforms to optimize usage trends and pipeline performance.

• Bachelors Degree in Computer Science Engineering Data Science or a related field.
• An MBA or advanced degree is a plus but not required.

(REQ ID: 1733