Senior Manager, Data Engineering

Jobgether SRL; India; Remote; INR 3,200,000 - 5,200,000; Full time

Benefits offered by this job

Fully remote in India

Senior leadership exposure

Career growth opportunities

Job summary

Jobgether SRL in India is seeking a Senior Manager, Data Engineering to lead high-performing data and ML teams in a fast-moving SaaS environment. You will own end-to-end data pipelines, production ML systems, analytics infrastructure, and data-driven product capabilities.

You will partner with Finance, Sales, Operations, Product, Platform, and Security to turn complex data into measurable business outcomes, drive governance, and set engineering standards in a remote-first setting.

Qualifications

• 8+ years in applied machine learning with leadership experience
• Proven track record managing 8+ engineers or professionals
• Experience with Salesforce, NetSuite, dbt, Fivetran, Snowflake, Databricks
• Strong SQL and software engineering principles, architecture and production operations
• Fluent in Python and ML frameworks (scikit-learn, PyTorch, TensorFlow)
• Experience leading production ML models and MLOps lifecycles
• Strong communication and stakeholder management in a fast-paced environment
• Experience with AI-assisted development tools and productivity tools

Responsibilities

• Lead data engineering, enterprise data apps, and ML teams with technical direction and people management
• Build end-to-end data pipelines for CRM/ERP data to centralized platforms
• Develop unified reporting models covering pipeline health, revenue, churn, and CLV
• Establish data governance, testing, modular data modeling, and single source of truth
• Translate metrics into business insights for executives and stakeholders
• Drive architecture, engineering best practices, and product quality improvements
• Lead ML engineers and data scientists from feature engineering to production
• Set standards for feature engineering, training, evaluation, and monitoring
• Collaborate with Product, Platform, and Security to turn signals into measurable outcomes
• Oversee SLAs, monitoring, on-call processes for data and model health
• Hire, coach, and grow teams across multiple levels in a remote-first setup
• Foster a collaborative, high-performing distributed engineering organization
• Promote continuous improvement and adoption of AI-assisted tools

Skills

Data Leadership

ML Engineering

Python

SQL

Cloud Platforms

Remote Leadership

Stakeholder Management

MLOps

Education

Bachelor's degree or higher in CS/EE

Tools

Snowflake

Databricks

dbt

Spark

Fivetran

Salesforce

NetSuite

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Manager, Data Engineering based in India.

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.

• Lead and guide engineering teams across data engineering, enterprise data applications, and machine learning, providing technical direction, delivery oversight, and people leadership.
• Build and operationalize end-to-end data pipeline architecture, including ingestion and transformation layers that move CRM and ERP data into centralized platforms such as Snowflake or Databricks.
• Partner with Finance, Sales, and Operations to develop unified reporting models covering pipeline health, recurring revenue, billing, churn, and customer lifetime value.
• Establish and enforce data governance and analytics engineering standards, including version control, automated testing, modular data modeling, and reliable single-source-of-truth practices.
• Act as a trusted technical advisor to senior and executive stakeholders, translating complex financial, operational, and technical metrics into clear business insights supported by reliable data.
• Collaborate with Staff and Principal Engineers to influence architecture, define engineering best practices, improve product quality, and deliver scalable features.
• Provide technical leadership across ML engineering and data science initiatives, ensuring models move from experimentation into reliable production systems rather than remaining one-off analyses.
• Set standards for feature engineering, model training, evaluation, serving, monitoring, rollback, and feedback loops that maintain model performance as product and threat patterns evolve.
• Partner with Product, Platform, and Security teams to translate identity, device, and telemetry signals into measurable outcomes such as precision, false-positive rates, and time-to-detect.
• Establish appropriate SLAs, monitoring, on-call practices, and operational processes for data and model health.
• Hire, onboard, coach, mentor, and manage a growing team, while supporting performance development and career progression across multiple levels of individual contributors.
• Lead teams effectively in a geographically distributed, remote-first environment and contribute to building a collaborative, high-performing engineering organization.
• Drive continuous improvement through innovation, process development, delivery excellence, reliability, and quality initiatives.
• Encourage effective use of AI coding agents and productivity tools to improve engineering workflows and maximize team effectiveness.

Requirements:

• 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.

Benefits:

• Competitive senior-level compensation aligned with experience and market expectations in India.
• Fully remote work within India as part of a remote-first working environment.
• Opportunity to lead and grow high-performing, geographically distributed engineering teams.
• Significant influence over engineering practices, architecture, product strategy, and execution.
• Opportunity to work on complex data, machine learning, identity, device, and telemetry systems at scale.
• Strong exposure to senior leadership and cross-functional collaboration across Product, Platform, Security, Finance, Sales, and Operations.
• Career growth opportunities through technical leadership, people management, and organizational impact.
• Collaborative environment that values innovation, continuous improvement, diverse perspectives, and strong human connections.
• Opportunity to incorporate modern AI tools into engineering and productivity workflows.
• Participation in engineering on-call rotations as part of maintaining reliable production systems.