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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.
Job Responsibility:
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
Requirements:
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 (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 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
Nice to have:
An MBA or advanced degree is a plus but not required
What we offer:
vibrant and dynamic work environment
multitude of benefits they can enjoy inside and outside of their work lives