Lead Data Integration Engineer

EPAM Systems; Colombia; On-site; COP 120,000,000 - 180,000,000; Full time

Benefits offered by this job

Healthcare benefits

Paid time off and sick leave

Upskilling and certification courses

LinkedIn Learning library access

Job summary

EPAM Systems is seeking a Lead Data Integration Engineer to lead analytics engineering and data modeling that turns raw interaction and telemetry data into trusted, consistent account datasets for decision-making and AI-enabled workflows. You will partner with cross-functional teams to deliver governed, self-service data products in Snowflake and dbt.

Responsibilities include designing dimensional models, building dbt models in Snowflake, establishing naming conventions, and delivering datasets

Qualifications

• 5+ years analytics engineering or data engineering experience.
• Data modeling experience for BI analytics and dimensional schemas.
• Strong leadership skills to define modeling standards and guide reviews.
• Strong project delivery skills in agile sprint cadences and backlog planning.
• Advanced SQL skills with CTEs, window functions, complex joins, and performance tuning.
• Strong dbt skills with modular projects, Jinja macros, custom tests, incremental models, and snapshots.
• Strong Snowflake skills including warehouse sizing, query profiling, clustering, Time Travel, and access control.
• Hands-on Git skills with branching, code reviews, and CI test runs.
• Strong stakeholder collaboration skills with analytics and operations partners.
• Upper-Intermediate English proficiency (B2).

Responsibilities

• Lead analytics engineering delivery for integrated account-level datasets across interaction and telemetry sources.
• Design dimensional models and semantic definitions that standardize account health, engagement, and intent metrics.
• Build dbt models in Snowflake that transform inputs into consistent dimensions and facts.
• Establish naming conventions, modeling patterns, and shared metric logic to prevent conflicting calculations.
• Create datasets optimized for retrieval and reasoning to support AI agent workflows and search use cases.
• Develop feature tables and context stores that enable automated meeting preparation and account research.
• Implement dbt tests, schema validations, and freshness monitoring to improve reliability and trust.
• Define governance controls including RBAC and auditability for sensitive pipeline and interaction data.
• Coordinate documentation, lineage, and ownership with operations and governance partners.
• Deliver self-service models and clear docs so analysts and product teams can query independently.
• Contribute to sprint planning, design reviews, and technical standards to ensure consistent execution.
• Use AI-assisted development tools to accelerate modeling, testing, and documentation work.

Skills

Analytics engineering

Data modeling

Leadership

Agile

SQL proficiency

dbt

Snowflake

Git

Stakeholder mgmt

English B2

Tools

Snowflake

dbt

Git

Job description

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 are seeking a Lead Data Integration Engineer to lead analytics engineering and data modeling that turns raw interaction and telemetry data into trusted, consistent account datasets for decision-making and AI-enabled workflows. You will partner with cross-functional teams to deliver governed, self-service data products in Snowflake and dbt.

Responsibilities

• Lead analytics engineering delivery for integrated account-level datasets across interaction and telemetry sources
• Design dimensional models and semantic definitions that standardize account health, engagement, and intent metrics
• Build dbt models in Snowflake that transform structured and unstructured inputs into consistent dimensions and facts
• Establish naming conventions, modeling patterns, and shared metric logic to prevent conflicting calculations
• Create datasets optimized for retrieval and reasoning to support AI agent workflows and search use cases
• Develop feature tables and context stores that enable automated meeting preparation and account research
• Implement dbt tests, schema validations, and freshness monitoring to improve reliability and trust
• Define governance controls including RBAC and auditability for sensitive pipeline and interaction data
• Coordinate documentation, lineage, and ownership with operations and governance partners
• Deliver self-service models and clear docs so analysts and product teams can query independently
• Contribute to sprint planning, design reviews, and technical standards to ensure consistent execution
• Use AI-assisted development tools to accelerate modeling, testing, and documentation work

Requirements

• 5+ years analytics engineering or data engineering experience
• Data modeling experience for BI analytics and dimensional schemas
• Strong leadership skills to define modeling standards and guide reviews
• Strong project delivery skills in agile sprint cadences and backlog planning
• Advanced SQL skills with CTEs, window functions, complex joins, and performance tuning
• Strong dbt skills with modular projects, Jinja macros, custom tests, incremental models, and snapshots
• Strong Snowflake skills including warehouse sizing, query profiling, clustering, Time Travel, and access control
• Hands-on Git skills with branching, code reviews, and CI test runs
• Strong stakeholder collaboration skills with analytics and operations partners
• Upper-Intermediate English proficiency (B2)

Nice to have

• Snowflake Cortex experience with search, LLM functions, or embeddings
• RAG applications development knowledge including chunking and retrieval strategies
• Python for data analytics skills such as Pandas and automation scripting
• Data governance tooling familiarity for metadata, lineage, and cataloging
• BI analytics and visualization experience designing models for Tableau, Looker, or Power BI

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.