Lead Data Engineer (DBT, Databricks, Azure)

Encora; United States; Hybrid; USD 140,000 - 190,000; Full time

Job summary

Coforge is seeking a Lead Data Engineer to own end-to-end delivery of strategic data products within a modern cloud data platform. You will design low-latency API-driven data services, build scalable Python backends, and manage data pipelines with Azure Databricks and DBT, while guiding a team of data and ML engineers.

You’ll drive architecture decisions, ensure data quality and observability, and lead CI/CD adoption. Open to LATAM-based candidates with strong leadership and communication skills.

Qualifications

• 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.
• Excellent Python programming with strong object-oriented principles.
• Extensive experience with PyTest, unit testing and software quality practices.
• Hands-on Azure Databricks and DBT expertise.
• Advanced SQL skills and data modeling knowledge.
• Experience with Terraform and IaC deployments.
• CI/CD pipelines, Git-based version control, and modern software engineering practices.
• Proven leadership in technical delivery while remaining hands-on.

Responsibilities

• Lead the RTS delivery squad and own end-to-end delivery of strategic data products on a modern cloud data platform.
• Design and oversee architecture of low-latency, API-driven data solutions.
• Build and maintain scalable backend services and REST APIs with Python and OOP.
• Develop data pipelines using Azure Databricks, DBT, SQL and cloud-native tech.
• Own curated data layers ensuring availability, scalability and performance.
• Lead Terraform-based infrastructure deployment and IaC practices.
• Mentor and develop a team of data and ML engineers; conduct code reviews and set standards.
• Collaborate with Product/Engineering/Business to define technical solutions and roadmaps.
• Ensure data quality, observability, monitoring, and SLA compliance across data products.
• Drive CI/CD adoption and oversee release management for pipelines and platform components.

Skills

Python

REST APIs

Azure Databricks

DBT

SQL

Terraform

Data Engineering

Data Modeling

CI/CD

Team Leadership

Job description

Job Title: Lead Data Engineer (DBT, Databricks, Azure)

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

Experience: 8+ years of experience.

Location: Open to candidates across LATAM.

At Coforge, we are looking for a Lead Data Engineer (#22145) with the following profile.

Responsibilities

• 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.

Mandatory Requirements

• 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.

Preferred Requirements

• Experience within insurance, financial services, or other highly regulated industries.
• Knowledge of insurance concepts such as policy administration, claims, underwriting, and customer data.
• Experience with Snowflake and Snowflake-to-Databricks integration or migration patterns.
• Hands-on experience with Azure AI Search, Lakebase, feature stores, or similar low-latency serving technologies.
• Experience with streaming and real-time data technologies such as Kafka, Event Hubs, or Delta Live Tables.
• Experience implementing data governance, security, and compliance frameworks.
• Experience managing large-scale DBT environments and terabyte-scale data pipelines.
• Experience leading cloud migration initiatives, particularly AWS-to-Azure migrations.
• Familiarity with machine learning platforms and collaboration with ML engineering teams.

Published on: 25-08-2026

At Coforge, we hire professionals solely based on their skills and qualifications and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality.