Senior Data Engineering Manager

Senior Engineering Manager – Data Engineering

Work Location: Gurgaon ( WFO)

About the Role

As an Engineering Manager – Data Engineering, you will lead and scale high-performing

data engineering teams responsible for building robust, scalable, and reliable data

platforms. You will define the data architecture, drive data platform strategy, and enable

data-driven decision-making across the organization.

This role requires a strong blend of technical expertise in data systems, people leadership,

and cross-functional collaboration to deliver high-impact data solutions that power

analytics, machine learning, and business intelligence.

Key Responsibilities

Team Leadership & Management

Build, mentor, and lead a team of 6–12 data engineers and platform engineers

Drive hiring, performance management, and career development

Foster a strong ownership-driven and data-first engineering culture

Data Platform & Architecture

Design and own scalable data pipelines, data lakes, and data warehouses

Define architecture for batch and real-time data processing systems

Ensure high availability, fault tolerance, and scalability of data systems

Data Engineering & Delivery

Oversee development of ETL/ELT pipelines and data workflows

Drive timely and high-quality delivery of data products and platform features

Partner with analytics, product, and ML teams to enable use cases

Data Governance & Quality

Establish best practices for data quality, lineage, governance, and security

Ensure compliance with data privacy and regulatory standards

Implement monitoring, alerting, and data validation frameworks

Collaboration & Stakeholder Management

Work closely with Product, Analytics, Risk, and Business teams

Translate business requirements into scalable data solutions

Communicate trade-offs, timelines, and technical decisions effectively

Platform Reliability & Optimization

Own SLAs/SLOs for data systems and pipelines

Optimize data infrastructure for cost, performance, and scalability

Lead incident management and root cause analysis for data issues

Innovation & Strategy

Evaluate and adopt modern data technologies and tools

Drive initiatives in real-time analytics, ML data pipelines, and data platform modernization

Continuously improve engineering practices and reduce tech debt

Qualifications

Bachelor's or Master's degree in Computer Science, Engineering, or related field.

10+ years of experience in engineering, with at least 3+ years in data engineering leadership

roles.

Strong Hands-on Experience In:

Programming: Python, Java, Scala

Data Processing: Apache Spark, Flink, Hadoop

Streaming: Kafka, Kinesis, Pub/Sub

Data Warehousing: BigQuery, Redshift, Snowflake

ETL Tools: Airflow, DBT, Luigi

Databases: MySQL, PostgreSQL, NoSQL systems

Cloud: AWS / GCP / Azure (data services ecosystem)

Additional Skills:

Experience building data lakes and lakehouse architectures

Strong understanding of data modeling (OLAP/OLTP, dimensional modeling)

Familiarity with ML pipelines and feature engineering

Expertise in data observability, monitoring, and governance frameworks

Strong stakeholder management and communication skills

Why Join Us

Opportunity to build and scale large-scale data platforms impacting millions of users

Work on cutting-edge fintech + data + analytics problems

Lead a high-impact team in a fast-paced, product-driven environment

Strong ownership, growth, and leadership exposure