Senior Manager, Data Engineering

This is a fully remote position, open to applicants in India.

📋 Description

• Lead the development team for EDA, ESE, and Machine Learning located in India.

• Oversee and mentor the engineering teams that report to this position.

• Design and implement comprehensive data pipeline architecture, facilitating the ingestion of Salesforce and NetSuite data into Snowflake/Databricks through Fivetran and dbt transformations.

• Collaborate with Finance, Sales, and Operations to create integrated reporting models for pipeline health, ARR, billings, churn, and Customer Lifetime Value.

• Uphold best practices in analytics engineering, including version control, automated testing in dbt, and modular data modeling.

• Provide counsel to C-suite executives, presenting financial and operational metrics supported by verified data models.

• Work alongside Staff and Principal Engineers to develop features, guide architecture, establish best practices, and enhance product quality.

• Shape engineering practices, product strategies, and execution efforts.

• Cooperate with engineering leadership and other departments to cultivate a world-class engineering organization.

• Offer technical leadership and supervision of team initiatives.

• Recruit, onboard, mentor, and develop a diverse and expanding team.

• Guide ML engineers and data scientists in delivering production models.

• Establish standards for feature engineering, training, evaluation, serving, and model feedback loops.

• Collaborate with product, platform, and security teams to convert identity, device, and telemetry signals into quantifiable outcomes.

• Set SLAs, monitoring, rollback, and on-call protocols for model health.

⛳️ Requirements

• Over 8 years of experience in applied ML, including several years in a managerial role and familiarity with a production MLOps environment.

• Proven experience leading a team of 8 or more members, encompassing performance management and team building.

• Proficiency with Salesforce, NetSuite, dbt, Fivetran, Snowflake, and Databricks.

• Strong understanding of SQL.

• Solid grasp of software engineering principles and methodologies.

• Demonstrated record of SaaS ownership and reliability principles.

• Practical experience working with agile teams.

• Effective communication skills with engineering managers and both technical and non-technical stakeholders.

• Ability to excel in a dynamic, collaborative environment.

• Proven history of continuous improvement through innovation, delivery, process development, and quality enhancement.

• Experience leading geographically diverse engineering teams in a remote-first setup.

• Familiarity with AI coding agents such as Cursor, Claude, or Copilot, as well as AI tools like Gemini and NotebookLM.

• Experience leading ML engineers and data scientists in deploying models to production.

• Knowledge of feature engineering, training, evaluation, serving, and model feedback loops.

• Proficient in Python, scikit-learn, PyTorch, TensorFlow, and large-scale data platforms like Spark or Snowflake.

• Ability to collaborate with product, platform, and security teams to translate identity, device, and telemetry signals into measurable results.

• Experience in hiring, coaching, and managing work across L3–L5 individual contributors, including SLAs, monitoring, rollback, and model-health on-call responsibilities.

• Bonus: Experience in commercial software development using Golang, C++, Python, Java, or other programming languages and operating system technologies.

• Bonus: Strong technical grounding in software engineering design principles.

• Bonus: In-depth understanding of statistical and ML concepts, such as supervised and unsupervised learning, anomaly detection, classification, ranking/scoring, model evaluation, and handling imbalanced datasets.

• Must reside in and be authorized to work in India.

• Fluency in both spoken and written English is essential.

• Engineers are expected to participate in on-call shifts.

🏝️ Benefits

• Remote-first work arrangement within India.

• Opportunities for career advancement.

• Collaborate with talented, supportive colleagues and an experienced executive team.

• Chance to influence engineering practices, product strategy, and execution.

• Equal opportunity employment.