Lead Data Software Engineer

EPAM Systems; México; Presencial; MXN 900.000 - 1.300.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Healthcare benefits

Paid time off

Upskilling programs

Global career opportunities

Volunteer opportunities

Descripción de la vacante

EPAM Systems seeks a Lead Data Software Engineer to join our global team and scale data-driven insights across platforms. You will work with machine learning datasets, ML models, and data pipelines to deliver reliable, API-enabled scoring and analytics.

You will lead a team, collaborate with Data Scientists, and shape data models, ETL/ELT workflows, and warehouse solutions using Databricks, Azure/AWS/GCP, and FastAPI. Fluency in English is required; remote options may apply.

Formación

• Bachelor's or Master's degree in Computer Science, Computer Engineering, Mathematics, Statistics, or an equivalent discipline.
• Five-plus years of practical, relevant professional background.
• Minimum one year of experience directing and managing teams.
• Experience within Machine Learning, Data Engineering, ML Infrastructure, or comparable domains, backed by strong grounding in probability, statistics, and machine learning fundamentals.
• Practical experience with Databricks, including Unity Catalog, plus cloud-based ML platforms such as Azure ML Studio, AWS, or GCP.
• Background constructing and expanding complete ML systems, ETL/ELT pipelines, and data workflows through Python, NumPy, Pandas, and SQL.
• Experience creating scalable APIs and microservices via FastAPI, working alongside Snowflake or similar data warehouse solutions.
• Effective communication and cross-departmental teamwork abilities, with working English fluency at B2 level or above, supporting clear comprehension of business requirements.

Responsabilidades

• Assist with and contribute to the creation of machine learning datasets and oversee scoring workflows.
• Develop and sustain thorough knowledge of both real-time and point-in-time data sources across the company, along with the Analytics staff who manage them.
• Collaborate with Data Scientists on the development and rollout of essential machine learning models.
• Push forward the ML dimension of the Enterprise Data Platform approach, broadening the reach of ML predictions and recommendations via API-driven scoring and warehouse-based access.
• Weave automated processes into ML Data Engineering pipelines to enable monitoring and alert generation.
• Implement tuning strategies and refine query performance for optimal efficiency.
• Function as a key point of contact for the Machine Learning team on Data Lifecycle Management topics.
• Remain informed about advancing technology trends spanning databases, data lakes, and warehouse solutions.
• Coordinate with Analytics colleagues to adhere to documented architecture, design, and deployment guidelines, maintaining policy alignment.
• Design and construct data models built for scalability and reuse.

Conocimientos

Machine Learning

Data Engineering

Python

SQL

FastAPI

Cloud platforms (Azure AWS GCP)

Educación

Bachelor's or Master's degree in Computer Science, Computer Engineering, Mathematics, Statistics

Herramientas

Databricks

Unity Catalog

Azure ML Studio

AWS

GCP

Snowflake

Python

NumPy/Pandas

SQL

FastAPI

Docker

Kubernetes

Descripción del empleo

EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.

We're currently seeking a Lead Data Software Engineer to join our organization. This role plays a central part in how the company generates, delivers, and expands data-driven insights at scale. You'll team up with talented specialists spanning multiple functions to develop creative solutions to intricate problems. It's an excellent match for someone who values pairing solid engineering discipline with genuine enthusiasm for data-informed decision making

Responsibilities

• Assist with and contribute to the creation of machine learning datasets and oversee scoring workflows
• Develop and sustain thorough knowledge of both real-time and point-in-time data sources across the company, along with the Analytics staff who manage them
• Collaborate with Data Scientists on the development and rollout of essential machine learning models
• Push forward the ML dimension of the Enterprise Data Platform approach, broadening the reach of ML predictions and recommendations via API-driven scoring and warehouse-based access
• Weave automated processes into ML Data Engineering pipelines to enable monitoring and alert generation
• Implement tuning strategies and refine query performance for optimal efficiency
• Function as a key point of contact for the Machine Learning team on Data Lifecycle Management topics
• Remain informed about advancing technology trends spanning databases, data lakes, and warehouse solutions
• Coordinate with Analytics colleagues to adhere to documented architecture, design, and deployment guidelines, maintaining policy alignment
• Design and construct data models built for scalability and reuse

Requirements

• Bachelor's or Master's degree in Computer Science, Computer Engineering, Mathematics, Statistics, or an equivalent discipline
• Five-plus years of practical, relevant professional background
• Minimum one year of experience directing and managing teams
• Experience within Machine Learning, Data Engineering, ML Infrastructure, or comparable domains, backed by strong grounding in probability, statistics, and machine learning fundamentals
• Practical experience with Databricks, including Unity Catalog, plus cloud-based ML platforms such as Azure ML Studio, AWS, or GCP
• Background constructing and expanding complete ML systems, ETL/ELT pipelines, and data workflows through Python, NumPy, Pandas, and SQL
• Experience creating scalable APIs and microservices via FastAPI, working alongside Snowflake or similar data warehouse solutions
• Effective communication and cross-departmental teamwork abilities, with working English fluency at B2 level or above, supporting clear comprehension of business requirements

Nice to have

• Background deploying production-grade workloads through Docker and Kubernetes, backed by solid understanding of scalable, dependable engineering practices
• Working knowledge of Microsoft Azure for developing and maintaining cloud-based solutions

We offer

• International projects with top brands
• Work with global teams of highly skilled, diverse peers
• Healthcare benefits
• Employee financial programs
• Paid time off and sick leave
• Upskilling, reskilling and certification courses
• Unlimited access to the LinkedIn Learning library and 22,000+ courses
• Global career opportunities
• Volunteer and community involvement opportunities
• EPAM Employee Groups
• Award-winning culture recognized by Glassdoor, Newsweek and LinkedIn

EPAM is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity or expression, disability, protected veteran status, or any other characteristic protected by applicable law.