Lead Data Integration Engineer

EPAM Systems, Inc.; United States; Remote; USD 140,000 - 190,000; Full time

Job summary

EPAM Systems, Inc. seeks a Lead Data Integration Engineer to lead analytics engineering and data modeling turning raw interaction and telemetry data into trusted account datasets. You will partner with cross-functional teams to deliver governed, self-service data products in Snowflake and dbt.

You design dimensional models, build dbt models, establish naming conventions, and drive AI-ready data workflows while ensuring governance and auditability across pipelines.

Qualifications

• 5+ years analytics engineering or data engineering experience.
• Data modeling for BI analytics and dimensional schemas.
• Strong leadership to define modeling standards and reviews.

Responsibilities

• Lead analytics engineering delivery for integrated account-level datasets.
• Design dimensional models and semantic definitions for metrics.
• Build dbt models in Snowflake transforming inputs to consistent facts.
• Establish naming conventions and shared metric logic to avoid conflicts.
• Create datasets for AI agent workflows and search use cases.
• Develop feature tables and context stores for account research.
• Implement dbt tests, schema validations, and freshness monitoring.
• Coordinate governance, RBAC, and data lineage with partners.
• Deliver self-service models with clear docs for analysts and product teams.

Skills

Analytics engineering

Data modeling

Leadership

SQL

dbt

Snowflake

Git

Stakeholder collaboration

English proficiency

Tools

Snowflake

dbt

Git

Tableau/Power BI

Job description

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.ResponsibilitiesLead analytics engineering delivery for integrated account-level datasets across interaction and telemetry sourcesDesign dimensional models and semantic definitions that standardize account health, engagement, and intent metricsBuild dbt models in Snowflake that transform structured and unstructured inputs into consistent dimensions and factsEstablish naming conventions, modeling patterns, and shared metric logic to prevent conflicting calculationsCreate datasets optimized for retrieval and reasoning to support AI agent workflows and search use casesDevelop feature tables and context stores that enable automated meeting preparation and account researchImplement dbt tests, schema validations, and freshness monitoring to improve reliability and trustDefine governance controls including RBAC and auditability for sensitive pipeline and interaction dataCoordinate documentation, lineage, and ownership with operations and governance partnersDeliver self-service models and clear docs so analysts and product teams can query independentlyContribute to sprint planning, design reviews, and technical standards to ensure consistent executionUse AI-assisted development tools to accelerate modeling, testing, and documentation workRequirements5+ years analytics engineering or data engineering experienceData modeling experience for BI analytics and dimensional schemasStrong leadership skills to define modeling standards and guide reviewsStrong project delivery skills in agile sprint cadences and backlog planningAdvanced SQL skills with CTEs, window functions, complex joins, and performance tuningStrong dbt skills with modular projects, Jinja macros, custom tests, incremental models, and snapshotsStrong Snowflake skills including warehouse sizing, query profiling, clustering, Time Travel, and access controlHands-on Git skills with branching, code reviews, and CI test runsStrong stakeholder collaboration skills with analytics and operations partnersUpper-Intermediate English proficiency (B2)Nice to haveSnowflake Cortex experience with search, LLM functions, or embeddingsRAG applications development knowledge including chunking and retrieval strategiesPython for data analytics skills such as Pandas and automation scriptingData governance tooling familiarity for metadata, lineage, and catalogingBI analytics and visualization experience designing models for Tableau, Looker, or Power BIWe offerInternational projects with top brandsWork with global teams of highly skilled, diverse peersHealthcare benefitsEmployee financial programsPaid time off and sick leaveUpskilling, reskilling and certification coursesUnlimited access to the LinkedIn Learning library and 22,000+ coursesGlobal career opportunitiesVolunteer and community involvement opportunitiesEPAM Employee GroupsAward-winning culture recognized by Glassdoor, Newsweek and LinkedIn