Job Description

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 a unified platform that seamlessly orchestrates data pipelines for ETL, ELT, and Reverse ETL (data activation)—eliminating the need for fragmented tools and enabling enterprises to move data efficiently across their ecosystem.

Responsibilities

• Develop and execute the product strategy for a unified data orchestration platform supporting ETL, ELT, and Reverse ETL 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.
• 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.
• Architect a self-service data virtualization platform that provides a self service experience.
• 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.

Requirements

• 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 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 (Denodo, Domo) 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.
• 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.

Benefits

• No benefits