Director, Product Management (Data Orchestration and Insights)

Workato delivers enterprise infrastructure for the agentic era, redefining iPaaS and helping enterprises unify data, applications, processes, and AI into a single, governed platform. A leader in Enterprise MCP and trusted by 50% of the Fortune 500, Workato’s cloud-native architecture connects every application, data source, and process to power real-time orchestration at scale. With enterprise-grade security and continuous innovation at its core, Workato provides the trusted foundation for organizations to automate with confidence and operationalize AI across the business. To learn more, visit www.workato.com

• 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 built-in transformation capabilities and integrations with tools like DBT and Coalesce to scale ELT pipelines efficiently.
• Ensure seamless data ingestion, movement, and activation across structured, semi-structured, and unstructured data formats.

• Embed data quality, lineage, governance, and operational analytics as core platform features, ensuring enterprises have built-in 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 go-to orchestration solution for large-scale deployments.

• Leverage AI to enhance data classification, transformation recommendations, and self-healing 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 Workato’s data services, driving continuous optimization and smarter decision-making.

• Architect a self-service data virtualization platform that provides a self service experience, enabling users to explore and analyze data from third-party apps, data warehouses, data lakes, Workato usage data, and custom datasets in real time.
• Develop interactive dashboards and AI-powered analytics that empower businesses to make data-driven decisions without deep technical expertise.
• Ensure seamless cross-platform data integration to unify enterprise data landscapes and drive deeper insights.

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

• 12+ 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 cross-functional teams, influencing product strategy, and driving execution in fast-paced 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 semi-structured data processing.
• Experience with data transformation tools (DBT, Coalesce) and orchestration frameworks (Airflow, Dagster) to build scalable pipelines.
• Knowledge of real-time 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.
• Hands-on experience with data virtualization and analytics platforms to enable seamless self-service data exploration and analytics.
• Strong background in cloud platforms (AWS, Azure, Google Cloud) and their data ecosystems.

• Experience integrating AI/ML-driven 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 real-time 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, user-friendly product capabilities.
• Skilled at collaborating with engineering, UX, security, legal, and go-to-market teams to drive enterprise adoption.

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

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