Chief Data Engineer

EPAM Systems; Colombia; Presencial; COP 120.000.000 - 180.000.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Healthcare benefits

Paid time off

Upskilling and certifications

LinkedIn Learning access

Global career opportunities

Volunteer and community involvement

Descripción de la vacante

EPAM Systems in Colombia is seeking a chief-level Chief Data Engineer to own end-to-end data modeling and pipeline delivery for a multi-phase enterprise data lake re-architecture on a modern AWS stack, coordinating with global teams to ensure scalable, secure data assets.

The role requires hands-on leadership in star-schema dimensional modeling, dbt testing, Databricks ETL/ELT development, and clear stakeholder communication, with a strong emphasis on data quality, documentation, and delivering

Formación

• 7+ years in data engineering with modern warehousing and lakehouse patterns.
• Hands-on SQL for analytics engineering and data validation.
• Experience with ETL/ELT across batch and incremental processing.
• Databricks in production environments.
• dbt for transformations, testing, and documentation.
• Senior stakeholder management with non-technical partners.
• End-to-end delivery ownership from requirements through deployment and support.
• Strong dimensional modeling using star schema (Kimball).
• Solid documentation skills (Confluence).
• Excellent written and verbal English (B2+).

Responsabilidades

• Lead dimensional data modeling with star schemas and fact/dimension design.
• Own end-to-end pipeline delivery from discovery to deployment and hypercare.
• Design ETL/ELT workflows to modernize warehousing to a lakehouse.
• Build and maintain transformations in dbt with tests and lineage.
• Develop data pipelines in Databricks with performance and scalability in mind.
• Collaborate with US-based stakeholders to elicit requirements and align on needs.
• Coordinate delivery across an engineering team with time-zone considerations.
• Validate data quality with SQL checks, unit tests, and UAT support.
• Document models, pipelines, and decisions for long-term maintainability.
• Provide basic dashboarding support to validate outputs.

Conocimientos

Data warehousing

SQL analytics

ETL/ELT pipelines

Databricks

dbt

Stakeholder management

End-to-end delivery

Dimensional modeling

Documentation

English proficiency

Herramientas

Databricks

dbt

Confluence

Descripción del empleo

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 looking for a chief-level Chief Data Engineer to own end-to-end data modeling and pipeline delivery for a multi-phase enterprise data lake re-architecture on a modern AWS stack. You will partner closely with stakeholders across time zones and drive outcomes with high autonomy.

Responsibilities

• Lead dimensional data modeling using star schemas, fact/dimension design, and aggregate-aware structures
• Own end-to-end pipeline delivery from requirements discovery through deployment and hypercare
• Design ETL/ELT workflows that evolve traditional warehousing practices into a modern lakehouse approach
• Build and maintain transformations in dbt with reliable tests, documentation, and lineage practices
• Develop data pipelines in Databricks with performance, scalability, and maintainability in mind
• Partner with US-based stakeholders to elicit requirements, clarify definitions, and anticipate future needs
• Coordinate delivery across an engineering team with time-zone overlap and ensure clear handoffs
• Validate data quality through SQL-based checks, unit tests, and UAT support
• Document models, pipelines, and decisions to enable alignment and long-term maintainability
• Provide basic dashboarding support to validate outputs and confirm business usability

Requirements

• 7+ years of data engineering experience with modern data warehousing and lakehouse patterns
• 7+ years of hands-on SQL experience for analytics engineering and data validation
• Experience with ETL/ELT solutions across batch and incremental processing
• Experience with Databricks in production environments
• Experience with dbt for transformations, testing, and documentation
• Senior stakeholder management experience working with non-technical partners
• End-to-end delivery ownership from requirements through deployment and support
• Strong dimensional modeling skills using star schema and Kimball methodology
• Strong documentation skills using collaboration tools (e.g., Confluence)
• Excellent communication skills for clear written updates and executive-ready narratives
• Upper-Intermediate English proficiency (B2, Upper-Intermediate)

Nice to have

• Apache Spark experience for large-scale distributed processing
• Experience with Tableau or Power BI for light visualization and validation
• HR domain exposure and ability to ramp quickly on HR data concepts
• Background with legacy BI/ETL tools such as Informatica, Cognos, or Business Objects
• Experience with traditional RDBMS platforms such as Oracle

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.