Senior Data Integration Engineer

EPAM Systems, Inc.; Colombia; A distancia; COP 120.000.000 - 200.000.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Healthcare benefits

Paid time off

Career development

Descripción de la vacante

EPAM Systems, Inc. seeks a Senior Data Integration Engineer to design and implement production data models in dbt and Snowflake, integrating CRM and interaction data to support QA, analytics, and AI agents.

You will build an enterprise semantic layer, enforce data governance, and collaborate with Revenue Operations to standardize metrics across platforms in a fast-paced, agile environment.

Formación

• 3+ years of experience in analytics engineering or data architecture.

Responsabilidades

• Build production data models in dbt and Snowflake to track account health and engagement velocity.
• Integrate structured and unstructured data (Salesforce, Gong, emails) into enterprise schemas.
• Create and maintain a semantic layer to unify metrics across tools.
• Develop metadata, lineage, and governance patterns; ensure data quality and freshness.
• Collaborate with governance teams and analysts to enable self-serve data access.

Descripción del empleo

We are seeking a Senior Data Integration Engineer to build production data models and semantic layers that serve both business teams analyzing account health and pipeline velocity and autonomous AI agents running automated meeting preparation, account research, and relationship tracking through Snowflake Cortex and Snowflake Intelligence.ResponsibilitiesBuild and maintain production data models in dbt and Snowflake that track account health, engagement velocity, and customer intent signalsCombine structured records and unstructured interaction data (Gong call transcripts, emails, Salesforce CRM objects, and product usage telemetry) into clean account-level dimensionsEstablish consistent modeling patterns, naming conventions, and metric definitions across GTM datasetsBuild and maintain an enterprise semantic layer (such as the dbt Semantic Layer or MetricFlow) to eliminate conflicting metric calculations across business toolsPrepare clean, context-rich datasets structured for retrieval, search, and reasoning within Snowflake Cortex, Snowflake Intelligence, and internal AI agentsDesign feature tables and context stores that power LLM agents for automated meeting prep, competitive intelligence, and account researchManage metadata and data enrichment patterns so AI agents correctly interpret account stages, customer sentiment, and relationship historyWrite automated tests, schema validations, and freshness monitors in dbt for both structured metrics and unstructured data transformationsMaintain data governance, role-based access controls (RBAC), and audit trails across sensitive sales pipeline and customer interaction dataPartner with Revenue Operations and governance teams to document data lineage and maintain clear dataset ownershipWork within an agile sprint cadence, contributing to backlog planning, design reviews, and technical standardsDeliver self-service data models and documentation that enable analysts and product teams to query data independentlyRequirements3+ years of commercial experience in analytics engineering, data engineering, or data architecture rolesProficiency in advanced SQL, including window functions, CTEs, complex joins, analytical queries, and execution plan optimization3+ years of production dbt experience, including modular project structure, Jinja macros, custom tests, incremental models, and snapshotsPractical experience with Snowflake, including virtual warehouse sizing, query profile analysis, clustering keys, Time Travel, zero-copy cloning, and access controlHands-on experience modeling B2B SaaS revenue and interaction data (Salesforce CRM, Gong, Marketo, or subscription billing data)Understanding of Kimball dimensional modeling (star schemas, slowly changing dimensions SCD 1/2/4, conformed dimensions) and semantic layer designDaily comfort with Git workflows, branching strategies, code reviews, and automated CI test runsFlexibility to use AI-assisted development tools (GitHub Copilot, Cursor, Claude Code) to speed up modeling work, test coverage, and documentationEnglish proficiency at B2 level or higherNice to havePractical experience or working familiarity with Snowflake Cortex AI functions (Cortex Search, LLM functions, embeddings)Familiarity with vector embeddings, chunking strategies, and retrieval-augmented generation (RAG) for conversational textWorking knowledge of Python for data manipulation (Pandas), API extraction, or pipeline automationExperience with metadata and lineage tools such as Alation, Collibra, DataHub, or dbt DocsExperience designing data models for self-service consumption in 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 LinkedInEPAM 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.