Senior Manager, Data Engineering

This is a senior technical leadership opportunity focused on building high-performing data engineering and machine learning teams in a fast-moving SaaS environment.
You will lead teams responsible for scalable data pipelines, production ML systems, analytics infrastructure, and data-driven product capabilities.
The role combines people leadership with hands-on technical oversight, architecture, engineering standards, and product strategy.
You will work closely with Finance, Sales, Operations, Product, Platform, Security, and senior engineering stakeholders to turn complex data into measurable business outcomes.
A major focus will be building reliable, governed, production-ready systems that support executive reporting, machine learning, and evolving product and threat requirements.
You will also shape engineering culture through hiring, mentoring, continuous improvement, and the adoption of modern AI-assisted development practices.
This role is ideal for a technically strong leader who enjoys going deep on architecture while developing diverse, high-performing teams across a remote-first environment.

• 8+ years of experience in applied machine learning, including several years of people management and experience operating production MLOps environments with versioned training pipelines, evaluation gates, model registries, and automated promotion to serving.
• Proven experience managing teams of 8 or more engineers or technical professionals, including performance management, hiring, mentoring, and building high-performing teams.
• Strong experience with data and analytics technologies such as Salesforce, NetSuite, dbt, Fivetran, Snowflake, and Databricks.
• Strong SQL skills and a solid understanding of software engineering principles, architecture, reliability, and production operations.
• Hands-on fluency in Python and experience with machine learning frameworks such as scikit-learn, PyTorch, or TensorFlow, alongside large-scale data platforms such as Spark, Snowflake, or equivalent technologies.
• Experience leading ML engineers and data scientists who deploy models into production and manage the complete lifecycle from feature engineering through monitoring and feedback.
• Strong understanding of statistical and machine learning concepts, including supervised and unsupervised learning, anomaly detection, classification, ranking/scoring, model evaluation, and imbalanced datasets.
• Demonstrated ownership of SaaS products or platforms, with a strong focus on reliability, operational excellence, and sustainable engineering practices.
• Experience working with agile teams and collaborating effectively with engineering managers, technical specialists, and non-technical business stakeholders.
• Proven ability to lead geographically distributed teams and operate successfully in a remote-first environment.
• Strong communication, stakeholder management, coaching, and organizational skills, with the ability to operate effectively in a fast-moving and collaborative environment.
• Experience with AI-assisted development tools such as Cursor, Claude, or Copilot, as well as productivity tools such as Gemini or NotebookLM, and the ability to apply them effectively to day-to-day work.
• Fluency in written and spoken English is required.
• Candidates must be located in and authorized to work in India.