Lead Data Engineer - API-Driven on Azure Databricks & DBT

Encora Inc.

Medellín

Presencial

COP 279.520.000 - 403.752.000

Jornada completa

Hace 3 días
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Descripción de la vacante

Coforge seeks a Lead Data Engineer to drive end-to-end data product delivery on a modern cloud platform. You will own architecture, guide a team of data and ML engineers, and collaborate with Product, Engineering, and Business stakeholders.

Expertise in Python, Azure Databricks, DBT, SQL, Terraform, and CI/CD, plus strong API design and data modeling, is required to build scalable, low-latency solutions with observable data pipelines and robust QA.

Formación

  • 8+ years of experience in Data Engineering, Software Engineering, or related technical roles.
  • At least 3 years of experience leading engineering teams, including senior, mid-level, and junior professionals.
  • Strong backend development experience with proven delivery of production-grade REST APIs and backend services.
  • Expert-level programming skills in Python, including strong object-oriented programming (OOP) principles.
  • Extensive experience with PyTest, unit testing, automated testing frameworks, and software quality practices.
  • Strong hands-on experience with Azure Databricks and DBT.
  • Advanced SQL skills and experience building scalable data solutions.
  • Deep understanding of data modeling, dimensional modeling, and consumption-oriented data architectures.
  • Extensive experience with Terraform and Infrastructure as Code (IaC) deployments.
  • Experience designing and delivering low-latency data products, serving layers, or API-driven data solutions.
  • Strong knowledge of CI/CD pipelines, Git-based version control, and modern software engineering practices.
  • Proven ability to lead technical delivery while remaining hands-on with architecture, development, and code reviews.
  • Excellent communication and stakeholder management skills, with the ability to work effectively across technical and business teams.

Responsabilidades

  • Lead the RTS delivery squad and own the end-to-end delivery of strategic data products within a modern cloud data platform.
  • Design and oversee the architecture of low-latency, API-driven data solutions, from backend data models through serving layers and API consumption.
  • Build and maintain scalable backend services and REST APIs using Python and object-oriented programming principles.
  • Design, develop, and optimize data pipelines using Azure Databricks, DBT, SQL, and cloud-native technologies.
  • Own the architecture and implementation of curated data layers, ensuring high availability, scalability, and performance.
  • Evaluate, select, and implement technologies for low-latency data serving and API consumption.
  • Lead infrastructure deployment and management using Terraform and Infrastructure as Code (IaC) practices.
  • Mentor and develop a team of data and machine learning engineers, providing technical guidance, coaching, and career development support.
  • Conduct code reviews and establish engineering standards, development best practices, and architectural guidelines.
  • Collaborate with Product, Engineering, Business, and Project stakeholders to define technical solutions and delivery roadmaps.
  • Ensure data quality, observability, monitoring, alerting, and SLA compliance across all data products and services.
  • Drive CI/CD adoption and oversee release management processes for pipelines, services, and platform components.
  • Act as the primary technical escalation point for troubleshooting complex production issues and ensuring long-term platform stability.
  • Maintain comprehensive technical documentation, architectural decisions, and implementation standards.

Conocimientos

Python
REST APIs
Azure Databricks
DBT
SQL
Terraform
Data Engineering
Data Modeling
CI/CD
Team Leadership

Herramientas

Python Tests (PyTest)

Descripción del empleo

Coforge seeks a Lead Data Engineer to drive end-to-end data product delivery on a modern cloud platform. You will own architecture, guide a team of data and ML engineers, and collaborate with Product, Engineering, and Business stakeholders.

Expertise in Python, Azure Databricks, DBT, SQL, Terraform, and CI/CD, plus strong API design and data modeling, is required to build scalable, low-latency solutions with observable data pipelines and robust QA.

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