Engineering Manager

PeopleStrong; India; On-site; INR 4,500,000 - 6,500,000; Full time

Benefits offered by this job

High-impact projects

Collaborative environment

Growth path to leadership

Job summary

PeopleStrong is seeking a Data Engineering Manager to lead a team of data engineers building scalable data platforms, pipelines, and analytics infrastructure for our clients. The role blends hands-on technical leadership with people management, requiring someone who can architect solutions, mentor engineers, and engage directly with client stakeholders.

Responsibilities include owning end-to-end delivery, defining best practices, collaborating with cross-functional teams, and guiding cloud

Qualifications

• 10+ years of overall experience, with 4+ years in a data engineering leadership/management capacity.
• Strong hands-on background in Spark, distributed computing, and modern data platforms (Databricks preferred).
• Deep expertise in at least one major cloud ecosystem (AWS, Azure, or GCP); working knowledge of a second is a plus.
• Proven experience architecting and delivering large-scale data pipelines (batch and streaming).
• Experience with CI/CD practices and MLOps fundamentals.
• Strong stakeholder management and client-facing consulting experience.
• Track record of building, scaling, and retaining high-performing engineering teams.
• Excellent communication skills — able to translate technical concepts for both engineering and business audiences.

Responsibilities

• Lead, mentor, and grow a team of data engineers (typically 6-12 members) across multiple client engagements.
• Own end-to-end delivery of data engineering projects — architecture, design, development, and deployment.
• Define and enforce best practices for data pipeline development, code quality, and CI/CD across the team.
• Collaborate with clients and cross-functional teams (data science, analytics, product) to translate business requirements into scalable data solutions.
• Drive technical decision-making on cloud platform selection, data architecture (batch/streaming), and tooling.
• Manage project timelines, resource allocation, and delivery risk across concurrent engagements.
• Conduct code/architecture reviews and ensure adherence to performance, security, and scalability standards.
• Own hiring, performance reviews, and career development for the team.
• Stay current on emerging data engineering trends (Databricks, Spark, cloud-native tools, MLOps) and evangelize adoption where relevant

Skills

Spark

Distributed computing

Data platforms

CI/CD

MLOps

Stakeholder management

Communication

Leadership

Tools

Databricks

AWS

Azure

GCP

Job description

Job Description

Job Description

We are looking for a Data Engineering Manager to lead a team of data engineers building scalable data platforms, pipelines, and analytics infrastructure for our clients. This role blends hands‑on technical leadership with people management, requiring someone who can architect solutions, mentor engineers, and engage directly with client stakeholders.

Key Responsibilities

• Lead, mentor, and grow a team of data engineers (typically 6-12 members) across multiple client engagements
• Own end-to-end delivery of data engineering projects — architecture, design, development, and deployment
• Define and enforce best practices for data pipeline development, code quality, and CI/CD across the team
• Collaborate with clients and cross-functional teams (data science, analytics, product) to translate business requirements into scalable data solutions
• Drive technical decision-making on cloud platform selection, data architecture (batch/streaming), and tooling
• Manage project timelines, resource allocation, and delivery risk across concurrent engagements
• Conduct code/architecture reviews and ensure adherence to performance, security, and scalability standards
• Own hiring, performance reviews, and career development for the team
• Stay current on emerging data engineering trends (Databricks, Spark, cloud-native tools, MLOps) and evangelize adoption where relevant

Required Skills & Experience

• 10+ years of overall experience, with 4+ years in a data engineering leadership/management capacity
• Strong hands‑on background in Spark, distributed computing, and modern data platforms (Databricks preferred)
• Deep expertise in at least one major cloud ecosystem (AWS, Azure, or GCP); working knowledge of a second is a plus
• Proven experience architecting and delivering large-scale data pipelines (batch and streaming)
• Experience with CI/CD practices and MLOps fundamentals
• Strong stakeholder management and client‑facing consulting experience
• Track record of building, scaling, and retaining high‑performing engineering teams
• Excellent communication skills — able to translate technical concepts for both engineering and business audiences

Good to Have

• Databricks / cloud certifications (Data Engineer Professional, Solutions Architect, etc.)
• Experience in a consulting or professional services environment
• Exposure to data governance, security, and compliance frameworks
• Prior experience mentoring engineers into senior/lead roles

What We Offer

• Opportunity to lead high-impact data engineering initiatives for marquee clients
• Collaborative, fast‑paced consulting environment
• Strong growth path into senior technical leadership roles