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JumpCloud is hiring a Senior Manager, Data Engineering to lead the EDA (Enterprise Data Architecture), ESE (Enterprise Systems Engineering), and Machine Learning development team in India. This is a people-management role where you will build and guide engineering teams, drive architecture decisions, define best practices, and enable product quality across data and ML initiatives.
Key Responsibilities:
- Manage and mentor engineering teams reporting to you, fostering high performance and career development
- Build end-to-end data pipeline architecture, operationalizing ingestion (Fivetran) and transformation (dbt) layers to move raw CRM (Salesforce) and ERP (NetSuite) data into central data environments (Snowflake/Databricks)
- Lead revenue operations alignment by partnering with Finance, Sales, and Operations to build unified reporting models spanning pipeline health, ARR, billings, churn, and Customer Lifetime Value (LTV)
- Enforce data governance and modeling standards, implementing soft-engineering best practices for analytics including version control, automated testing via dbt, and modular data modeling
- Serve as a trusted advisor to C-suite leaders, presenting complex financial and operational performance metrics backed by audited data models
- Interact with Staff and Principal engineers to build features, drive architecture, and define best practices
- Provide technical leadership and oversight of team activities in your areas of expertise
- Hire, onboard, and mentor a growing and diverse team of high-potential team members
- Partner with peers and other teams to build and inspire a world-class engineering organization
- Lead ML engineers and data scientists who ship models to production, setting the bar for feature engineering, training, evaluation, and serving
- Hire, coach, and sequence work across L3–L5 individual contributors with clear SLAs, monitoring, rollback, and on-call responsibilities for model health
The role involves working with AI tools to maximize team potential and requires participation in on-call shifts for production support.
Requirements:
- 8+ years in applied ML, including several years managing people and experience with production MLOps environments (versioned training pipelines, evaluation gates, model registry, automated promotion to serving)
- Experience managing a team of 8 or more members, with demonstrated performance management and team-building success
- Experience with Salesforce, NetSuite, dbt, Fivetran, Snowflake, and Databricks
- Strong SQL skills
- Strong understanding of software engineering principles and techniques
- Track record of Software-as-a-Service ownership and commitment to reliability principles
- Hands-on experience working with agile teams
- Ability to work and communicate effectively with other engineering managers and both technical and non-technical business stakeholders
- Proven ability to thrive in fast-moving, team-oriented, collaborative environments
- Track record of continuous improvement through innovation, delivery, process development, and quality
- Experience leading geographically diverse engineering teams in remote-first work environments
- Exposure to AI coding agents (Cursor, Claude, Copilot) and AI tools (Gemini, Notebook LLM) with effective usage for day-to-day work optimization
- Hands-on fluency in Python, scikit-learn/PyTorch/TensorFlow, and large-scale data platforms (Spark, Snowflake, or equivalent)
- Ability to go deep on architecture when design or incidents require it
- Fluent English for interviews and internal business communication
Bonus:
- Commercial software development in multiple languages and operating systems (Golang, C++, Python, Java, etc.)
- Strong technical foundation in software engineering design principles
- Strong understanding of statistical and ML concepts including supervised/unsupervised learning, anomaly detection, classification, ranking/scoring, model evaluation, and handling imbalanced datasets
