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Data Engineer- Customer Recommender

Reads like a ML Engineer role: putting models into production.

Pune, Maharashtra, India

Live, first seen by us 29 days ago
Pay
Pay not listed
Work setting
On-site — work setting source
Work setup in the employer’s posting: On-site
From the employer’s posting
Employment
Full-time — employment source
Employment type in the employer’s posting: Full-time
From the employer’s posting

What you’ll work on

Full posting
  • Design and optimize end-to-end ML pipelines for training, testing and deployment

  • Monitor deployed models for performance, accuracy and drift

  • Turn experimental models into production-grade solutions with data scientists

  • Create and maintain APIs that deliver ML results to internal teams and customers

  • Mentor and support junior engineers and data scientists

From the employer’s posting
Design and optimize end-to-end machine learning pipelines for training, testing, and deployment in production environments
implement monitoring solutions to track performance, accuracy, and drift over time
Collaborate with data scientists to transition experimental models to production-grade solutions
Create and maintain APIs or other interfaces to deliver machine learning results to internal teams and Metro’s customers
Mentor and support junior engineers and data scientists, enabling their growth and success

What you’ll bring

All qualifications

Core experience

  • 8 years of hands-on experience in building and deploying machine learning models in production.
  • Proven experience in leading or mentoring technical teams;
  • Proficiency in Python, Go and machine learning frameworks;
  • Strong understanding of MLOps tools and practices, including CI/CD pipelines, model versioning, and monitoring;
  • Proficient with data transformation tools (preferable dbt);
  • Expertise in GCP services such a Cloud Run, Kubernetes, BigQuery and VertexAI;
Qualification wording
8 years of hands-on experience in building and deploying machine learning models in production. Strong technical background and current modern BI and reporting technologies;
Proven experience in leading or mentoring technical teams;
Proficiency in Python, Go and machine learning frameworks;
Strong understanding of MLOps tools and practices, including CI/CD pipelines, model versioning, and monitoring;
Proficient with data transformation tools (preferable dbt);
Expertise in GCP services such a Cloud Run, Kubernetes, BigQuery and VertexAI;
Apply at METRO/MAKRO

Posting record

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Status in our records
Live
First seen by us
Oct 5, 202629 days ago
Recorded sightings
311
Last seen by us
Nov 4, 2026
Employer says posted
Sep 29, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 29

Similar jobs usually come down between day 6 and day 69.

From 4,296 similar postings that came down. Coming down is not always a hire.

METRO/MAKRO is hiring

5 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Hiring at a steady pace
  • Takes jobs down quickly
  • 20% of open jobs were reposted
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • BigQuery
  • dbt
  • GCP
  • Kubernetes
  • Go
Where the posting names them
- Proven experience in leading or mentoring technical teams; - Proficiency in Python, Go and machine learning frameworks; - Strong understanding of MLOps tools and practices, including CI/CD pipelines, model versioning, and monitoring;
- Proficient with data transformation tools (preferable dbt); - Expertise in GCP services such a Cloud Run, Kubernetes, BigQuery and VertexAI; - Solid skills in API development and automated testing;
- Strong understanding of MLOps tools and practices, including CI/CD pipelines, model versioning, and monitoring; - Proficient with data transformation tools (preferable dbt); - Expertise in GCP services such a Cloud Run, Kubernetes, BigQuery and VertexAI;

Your next step

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About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

View original posting ↗

Job Description

Your Responsibilities:   

  • Take ownership of the technical direction and execution of machine learning projects within the Data Science team; 
  • Mentor and support junior engineers and data scientists, enabling their growth and success;
  • Establish best practices for software design, architecture, and MLOps;
  • Design and optimize end-to-end machine learning pipelines for training, testing, and deployment in production environments;
  • Ensure seamless deployment of machine learning models and implement monitoring solutions to track performance, accuracy, and drift over time;
  • Collaborate with data scientists to transition experimental models to production-grade solutions;
  • Work closely with other software/data engineers and product teams to ensure effective delivery of machine learning products;
  • Collaborate with other teams and gather requirements to solve complex customer problems with machine learning;
  • Maintain and scale machine learning infrastructure using GCP;
  • Implement robust security measures to protect data privacy;
  • Create and maintain APIs or other interfaces to deliver machine learning results to internal teams and Metro’s customers;
  • Evaluate emerging machine learning technologies, frameworks, and trends, and introduce improvements to existing workflows.  

Qualifications

Required key competencies and qualifications: 

  • 8 years of hands-on experience in building and deploying machine learning models in production. Strong technical background and current modern BI and reporting technologies; 
  • Proven experience in leading or mentoring technical teams;
  • Proficiency in Python, Go and machine learning frameworks; 
  • Strong understanding of MLOps tools and practices, including CI/CD pipelines, model versioning, and monitoring;
  • Proficient with data transformation tools (preferable dbt);
  • Expertise in GCP services such a Cloud Run, Kubernetes, BigQuery and VertexAI;
  • Solid skills in API development and automated testing;
  • Exceptional problem-solving abilities and a proactive, team-oriented mindset;
  • Strong communication and collaboration skills, with the ability to explain technical concepts to non-technical stakeholders;
  • Leadership qualities with a track record of driving projects and guiding teams toward success;
  • Experience in optimizing models for performance (e.g., inference speed, resource usage);
  • Understanding of ethical AI, bias mitigation, and data privacy principles. 

Company Description

Metro Global Solution Center (MGSC) is internal solution partner for METRO, a €31 Billion international wholesaler with operations in more than 30 countries. The store network comprises a total of 623 stores in 21 countries, of which 522 offer out-of-store delivery (OOS), and 94 dedicated depots. In 12 countries, METRO runs only the delivery business by its delivery companies (Food Service Distribution, FSD). 

HoReCa and Traders are core customer groups of METRO. The HoReCa section includes hotels, restaurants, catering companies as well as bars, cafés and canteen operators. The Traders section includes small grocery stores and kiosks. The majority of all customer groups are small and medium-sized enterprises as well as sole traders. METRO helps them manage their business challenges more effectively. 

MGSC, location wise is present in Pune (India), Düsseldorf (Germany) and Szczecin (Poland). We provide HR, Finance, IT & Business operations support to 31 countries, speak 24+ languages and process over 18,000 transactions a day. We are setting tomorrow’s standards for customer focus, digital solutions, and sustainable business models. For over 10 years, we have been providing services and solutions from our two locations in Pune and Szczecin. This has allowed us to gain extensive experience in how we can best serve our internal customers with high quality and passion. We believe that we can add value, drive efficiency, and satisfy our customers.

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Pune, Maharashtra, India

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