Data Engineer- Customer Recommender

METRO Global Solution Center IN; Maharashtra; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Metro Global Solution Center (MGSC) is the internal solution partner for METRO. MGSC provides HR, Finance, IT and Business operations support across 31 countries, delivering scalable ML solutions.

This role leads the technical direction for ML projects, mentors engineers and data scientists, and ensures production-grade deployment with robust monitoring and security. Applicants should have 8+ years of ML production experience, strong Python and Go skills, and deep knowledge of MLOps, GCP, and

Qualifications

• 8 years 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 (dbt).
• Expertise in GCP services such as 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.

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.

Skills

Python

Go

Machine learning

MLOps

CI/CD

API development

dbt

Leadership

Communication

Problem solving

Tools

GCP

Kubernetes

BigQuery

VertexAI

Job 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.

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.

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.