Data Engineering Manager - Enterprise Data Platform

Talent et au-dela; Navi Mumbai; On-site; INR 3,500,000 - 6,500,000; Full time

Job summary

Talent et au-dela is seeking an Data Engineering Manager to lead the Enterprise Data Platform team in Navi Mumbai. You will drive data architecture, pipelines, and governance while mentoring a growing team of data engineers across cloud environments such as Snowflake, AWS, Azure, and GCP.

You will collaborate with cross-functional leaders to align data strategy with business objectives, promote operational rigor, and deliver scalable data solutions built for AI-enabled analytics.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• 8+ years of experience in data engineering or related roles, including at least 2–3 years of leadership experience managing technical teams.
• Proven experience designing and maintaining large-scale data architectures, pipelines, and data models in cloud environments (e.g., Snowflake, AWS, Azure, or GCP)
• Advanced proficiency in SQL and Python for data manipulation, transformation, and automation
• Deep understanding of ETL/ELT frameworks, data orchestration tools (e.g., Airflow), and distributed messaging systems (e.g., Kafka)
• Strong knowledge of data governance, quality, and compliance frameworks
• Experience working with enterprise data sources (CRM, ERP, Marketing Automation, Financial Systems, etc.) is preferred
• Hands-on experience with AI/ML platforms, model deployment, or data-driven automation is a strong plus
• Excellent communication and stakeholder management skills with the ability to translate complex data concepts into business value
• Demonstrated ability to build high-performing teams and lead through change

Responsibilities

• Lead, mentor, retain top talent and develop a team of data engineers, fostering a culture of excellence, accountability, and continuous improvement
• Define and drive the data engineering roadmap aligned with enterprise data strategy and business objectives
• Collaborate with senior technology and business leaders to define data platform priorities, architecture, and long‑term vision
• Promote a culture of innovation, operational rigor, and customer empathy within the data organization
• Oversee the design, development, and maintenance of high‑quality data pipelines and ELT/ETL workflows across enterprise systems and Client Team’s platform
• Ensure scalable, secure, and reliable data architectures using modern cloud technologies (e.g., Snowflake, Airflow, Kafka, Docker)
• Lead AI learning initiatives and integrate AI/ML‑driven solutions into data products to enhance automation, predictive insights, and decision intelligence
• Champion data quality, governance, lineage, and compliance standards across the enterprise data ecosystem
• Partner with engineering and infrastructure teams to optimize data storage, compute performance, and cost efficiency
• Support career development through mentoring, skill‑building, and performance feedback

Skills

Airflow

Kafka

Snowflake

Python

SQL

Team Handling: 4+ members for the last

Education

Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field

Tools

AWS

Azure

GCP

Docker

dbt

Job description

Data Engineering Manager - Enterprise Data Platform

Job Overview

As a Data Engineering Manager within the Enterprise Data Platform team at Client team, you will lead a team of skilled data engineers responsible for building and optimizing data pipelines, managing large-scale data models, and ensuring the quality, availability, and performance of enterprise data assets. This leadership role combines technical depth,strategic thinking, and people management to enable Client team’s data-driven decision-making and analytics capabilities.

You’ll collaborate closely with cross-functional partners across Technology & Engineering, Product, Sales, Marketing, Research, Finance, and Administration to deliver robust, scalable data solutions. The ideal candidate is a hands‑on leader with a strong background in modern data platforms, cloud architecture, and team development—someone passionate about empowering teams and improving data capabilities across the organization. A core part of this role is shaping an analytics environment that is built for AI agents as much as for people. Our analysts, executives and AI agents should all query the same governed, documented, well‑described data and get the same answers. You will lead the team to make that real, with semantic layers, governed metrics, rich metadata, agent‑ safe access, and evaluation of agent output, and in using agents to build faster and with higher quality.

This is both a strategic and hands‑on leadership role: you will guide architectural decisions, mentor engineers, collaborate with cross-functional leaders, and contribute to building next-generation data and AI capabilities at client teams. You will exhibit a growth mindset, be willing to solicit feedback, engage others with empathy, and help create a culture of belonging, teamwork, and purpose. If you love leading a team of passionate data engineers, building data-centric solutions, strive for excellence every day, are adaptable and focused, and believe work should be fun, come join us!

Primary Job Responsibilities

• Lead, mentor, retain top talent and develop a team of data engineers, fostering a culture of excellence, accountability, and continuous improvement
• Define and drive the data engineering roadmap aligned with enterprise data strategy and business objectives
• Collaborate with senior technology and business leaders to define data platform priorities, architecture, and long‑term vision
• Promote a culture of innovation, operational rigor, and customer empathy within the data organization
• Oversee the design, development, and maintenance of high‑quality data pipelines and ELT/ETL workflows across enterprise systems and Client Team’s platform
• Ensure scalable, secure, and reliable data architectures using modern cloud technologies (e.g., Snowflake, Airflow, Kafka, Docker)
• Lead AI learning initiatives and integrate AI/ML‑driven solutions into data products to enhance automation, predictive insights, and decision intelligence
• Champion data quality, governance, lineage, and compliance standards across the enterprise data ecosystem
• Partner with engineering and infrastructure teams to optimize data storage, compute performance, and cost efficiency
• Support career development through mentoring, skill‑building, and performance feedback

Experience, Skills and Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field
• 8+ years of experience in data engineering or related roles, including at least 2–3 years of leadership experience managing technical teams
• Proven experience designing and maintaining large‑scale data architectures, pipelines, and data models in cloud environments (e.g., Snowflake, AWS, Azure, or GCP)
• Advanced proficiency in SQL and Python for data manipulation, transformation, and automation
• Deep understanding of ETL/ELT frameworks, data orchestration tools (e.g., Airflow), and distributed messaging systems (e.g., Kafka)
• Strong knowledge of data governance, quality, and compliance frameworks
• Experience working with enterprise data sources (CRM, ERP, Marketing Automation, Financial Systems, etc.) is preferred
• Hands‑on experience with AI/ML platforms, model deployment, or data‑driven automation is a strong plus
• Excellent communication and stakeholder management skills with the ability to translate complex data concepts into business value
• Demonstrated ability to build high‑performing teams and lead through change

Must have skills :

• Airflow
• Kafka
• Snowflake
• Python
• SQL
• Team Handling: 4+ members for the last 3 years

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