Lead Data Software Engineer

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.

Work arrangement
Yes