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EPAM Systems / Software

Lead Data Integration Engineer

nuevaDesde Argentina

  • Argentina
  • Tiempo completo
  • Modalidad no informada
  • Lead
  • 5+ años de experiencia

Requisitos

  • sql
  • inteligencia artificial
  • análisis de datos
  • b2b
  • crm
  • facturación
  • • 5+ años de experiencia
  • • inglés b2

Suma si tenés

  • python
  • power bi
  • tableau
  • looker

La búsqueda

We are seeking a Lead Data Integration Engineer to deliver production dbt and Snowflake models powering GTM analytics and AI agents. You will create trusted semantic layers, unify Salesforce and Gong-style interaction data, and prepare datasets for Snowflake Cortex and Snowflake Intelligence.

Responsibilities

• Design and maintain production data models in dbt and Snowflake to measure account health, engagement velocity, and customer intent signals

• Integrate structured records with unstructured interaction data (Gong call transcripts, emails, Salesforce CRM objects, and product usage telemetry) into reliable account-level dimensions

• Define consistent modeling patterns, naming conventions, and metric definitions across GTM datasets

• Implement and operate an enterprise semantic layer (such as the dbt Semantic Layer or MetricFlow) to prevent conflicting metric calculations across business tools

• Prepare clean, context-rich datasets optimized for retrieval, search, and reasoning in Snowflake Cortex, Snowflake Intelligence, and internal AI agents

• Create feature tables and context stores that enable LLM agents for automated meeting prep, competitive intelligence, and account research

• Administer metadata and data enrichment patterns so AI agents correctly interpret account stages, customer sentiment, and relationship history

• Develop automated tests, schema validations, and freshness monitors in dbt for both structured metrics and unstructured data transformations

• Enforce data governance, role-based access controls (RBAC), and audit trails across sensitive sales pipeline and customer interaction data

• Collaborate with Revenue Operations and governance teams to document data lineage and maintain clear dataset ownership

• Contribute within an agile sprint cadence, supporting backlog planning, design reviews, and technical standards

• Deliver self-service data models and documentation so analysts and product teams can query data independently

Requirements

• Proven track record with 5+ years of commercial experience in analytics engineering, data engineering, or data architecture roles

• Expert-level proficiency in advanced SQL, including window functions, CTEs, complex joins, analytical queries, and execution plan optimization

• Extensive hands-on experience with 5+ years of production dbt work, including modular project structure, Jinja macros, custom tests, incremental models, and snapshots

• Solid practical experience with Snowflake, including virtual warehouse sizing, query profile analysis, clustering keys, Time Travel, zero-copy cloning, and access control

• Demonstrated experience modeling B2B SaaS revenue and interaction data (Salesforce CRM, Gong, Marketo, or subscription billing data)

• Deep understanding of Kimball dimensional modeling (star schemas, slowly changing dimensions SCD 1/2/4, conformed dimensions) and semantic layer design

• Daily comfort with Git workflows, branching strategies, code reviews, and automated CI test runs

• Willingness to use AI-assisted development tools (GitHub Copilot, Cursor, Claude Code) to accelerate modeling work, test coverage, and documentation

• English proficiency at B2 (Upper-Intermediate) level or higher

Nice to have

• Working familiarity with Snowflake Cortex AI functions (Cortex Search, LLM functions, embeddings)

• Understanding of vector embeddings, chunking strategies, and retrieval-augmented generation (RAG) for conversational text

• Working knowledge of Python for data manipulation (Pandas), API extraction, or pipeline automation

• Experience with metadata and lineage tools such as Alation, Collibra, DataHub, or dbt Docs

• Background designing self-service data 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

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