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32 Dunnhumby Jobs
Big Data Engineering Manager| ML ops
13-14 years
₹ 32.3 - 32.3L/yr (AmbitionBox estimate)
This is an estimate of the average salary range for this
position. It has not been reviewed by the company, and
the actual salary may differ.
Gurgaon / Gurugram
1 vacancy
Big Data Engineering Manager| ML ops
Dunnhumby
posted 2mon ago
Job Role Insights
Flexible timing
Key skills for the job
Job Description
dunnhumby is the global leader in Customer Data Science, empowering businesses everywhere to compete and thrive in the modern data-driven economy. We always put the Customer First.
Our mission: to enable businesses to grow and reimagine themselves by becoming advocates and champions for their Customers. With deep heritage and expertise in retail - one of the world s most competitive markets, with a deluge of multi-dimensional data - dunnhumby today enables businesses all over the world, across industries, to be Customer First.
dunnhumby employs nearly 2,500 experts in offices throughout Europe, Asia, Africa, and the Americas working for transformative, iconic brands such as Tesco, Coca-Cola, Meijer, Procter Gamble and Metro.
We are seeking a highly motivated and experienced Big Data Engineering Manager to lead the design, development, and delivery of robust, scalable data processing platforms. This leadership role involves overseeing the end-to-end execution of big data solutions while fostering innovation, ensuring high performance, and driving alignment with business goals. The ideal candidate will have a proven track record in managing technical teams, implementing distributed systems, and delivering high-quality big data architectures.
This leadership role within the Retail Media Platform is designed to address the evolving challenges of modern grocery retail. By unlocking new revenue streams, driving sales growth, and fostering stronger customer connections, this role is pivotal to shaping the future of retail media. Our team is committed to empowering brands and retailers to measure the impact of advertising across all channels with precision and efficiency, leveraging best-in-class dunnhumby customer data science to deliver seamless, data-driven insights.
Key Responsibilities
Platform Development Delivery
- Architect and deliver scalable data processing platforms for batch and streaming workflows.
- Develop ETL pipelines, data ingestion frameworks, and data lake solutions.
- Optimize platforms for performance, reliability, and scalability in cloud and hybrid environments.
Collaboration Stakeholder Engagement
- Partner with product, analytics, and business teams to define data platform needs.
- Act as the technical liaison between business goals and engineering execution.
Technical Expertise
- Build distributed data systems with tools like Spark, Flink, Kafka, and Hive.
- Ensure data platform designs meet security and compliance standards.
- Champion modern architecture practices, including serverless and event-driven designs.
Process Quality Assurance
- Establish best practices for CI/CD, testing, and code reviews.
- Implement robust monitoring and observability frameworks.
Team Leadership Management
- Lead and mentor a team of data engineers, fostering growth and performance.
- Cultivate a culture of innovation, collaboration, and excellence.
Innovation Continuous Improvement
- Evaluate and integrate emerging technologies to enhance platform capabilities.
- Drive continuous improvement in engineering practices and infrastructure.
Skills Qualifications
Must-Have Skills
- Leadership: Proven experience in scaling and managing data engineering teams.
- Big Data Tools: Hands-on expertise with Spark, Kafka, Hive, and Airflow.
- Cloud Platforms: Proficiency in GCP, AWS, or Azure for big data solutions.
- Data Architecture: Experience designing scalable, distributed data platforms.
- Programming: Advanced skills in Python, Java, or Scala.
- Processing Workflows: Expertise in building real-time and batch data pipelines.
- DevOps: Proficiency in CI/CD, Docker, Kubernetes, and Terraform.
- Data Governance: Understanding of frameworks like GDPR and CCPA.
- Problem Solving: Ability to tackle complex challenges with innovative solutions.
- Communication: Strong skills to align cross-functional stakeholders.
Nice-to-Have Skills
- Experience with ML Ops frameworks (e.g., Kubeflow, Vertex AI).
- Knowledge of metadata management and data cataloging tools.
- Familiarity with event-driven architectures and streaming frameworks.
- Expertise with cloud-native big data services like BigQuery, Redshift, or Snowflake.
What you can expect from us
We won t just meet your expectations. We ll defy them. So you ll enjoy the comprehensive rewards package you d expect from a leading technology company. But also, a degree of personal flexibility you might not expect. Plus, thoughtful perks, like flexible working hours and your birthday off.
You ll also benefit from an investment in cutting-edge technology that reflects our global ambition. But with a nimble, small-business feel that gives you the freedom to play, experiment and learn.
And we don t just talk about diversity and inclusion. We live it every day - with thriving networks including dh Gender Equality Network, dh Proud, dh Family, dh One and dh Thrive as the living proof. We want everyone to have the opportunity to shine and perform at your best throughout our recruitment process. Please let us know how we can make this process work best for you. For .
Our approach to Flexible Working
At dunnhumby, we value and respect difference and are committed to building an inclusive culture by creating an environment where you can balance a successful career with your commitments and interests outside of work.
We believe that you will do your best at work if you have a work / life balance. Some roles lend themselves to flexible options more than others, so if this is important to you please raise this with your recruiter, as we are open to discussing agile working opportunities during the hiring process.
For further information about how we collect and use your personal information please see our Privacy Notice which can be found (here)
Employment Type: Full Time, Permanent
Read full job descriptionPrepare for Data Engineering Manager roles with real interview advice
Top Dunnhumby Data Engineering Manager Interview Questions
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What people at Dunnhumby are saying
Data Engineering Manager salary at Dunnhumby
reported by
2
employees
with 13-14
years exp.
Unlock
₹29.1
L/yr - ₹37.1
L/yr
11%
less
than the average Data Engineering Manager Salary in India
View more details
What Dunnhumby employees are saying about work life
based on 162 employees
Flexible timing
Monday to Friday
No travel
Day Shift
Dunnhumby Benefits
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