Lead Data Engineer

Encora; Colombia; Remote; COP 453,118,000 - 582,581,000; Full time

Job summary

Coforge is looking for a Lead Data Engineer to guide data engineering teams remotely. You will own the architecture, drive large-scale data platforms, and oversee migrations from Snowflake/SSIS to Azure Databricks and DBT.

Minimum 8+ years in data engineering with leadership experience; strong SQL, Python, and cloud/IaC skills are required. Prior experience in insurance/financial services is a plus.

Qualifications

• 8+ years in data engineering with 2-3+ years in a lead or staff role.
• Experience owning system design for large-scale data platforms.
• Hands-on with Snowflake, Azure Databricks, DBT, Python processing terabytes daily.
• Strong SQL, data modeling, and ETL/ELT knowledge.
• Terraform and IaC experience; cloud migrations AWS→Azure.
• Leadership in mentoring and developing teams; insurance/financial services exposure preferred.
• Knowledge of security, governance, observability, and data quality frameworks.

Responsibilities

• Lead data engineering teams and set technical direction.
• Own end-to-end architecture and production-ready delivery.
• Define and drive data migration strategies from Snowflake/SSIS to Azure Databricks and DBT.
• Oversee scalable data pipelines, data models, Terraform, CI/CD, observability, and platform stability across Azure and legacy environments.
• Mentor teams and collaborate with stakeholders in insurance/finance domains.

Skills

Data engineering

Lead experience

Snowflake

Azure Databricks

DBT

Python

Terraform

CI/CD

SQL

Data modeling

ETL/ELT

Distributed systems

Mentoring

Tools

Terraform

Git

CI/CD tooling

Job description

Experience: 8+ YOE.

Mode: Remote.

We at Coforge are hiring Lead Data Engineer (#16277-1-1) with the following skill set.

Key Responsibilities

Lead and mentor data engineering teams while setting technical direction, conducting code reviews, and driving engineering excellence.

Own the end-to-end architecture, design, and implementation of scalable and reliable data platforms, ensuring production-ready delivery.

Define and drive data migration strategies from Snowflake/SSIS to Azure Databricks and DBT, including architecture decisions and execution oversight.

Oversee scalable data pipelines, data models, Terraform infrastructure, CI/CD, data integration, observability, and platform stability across Azure and legacy environments.

Required Skills & Qualifications

8+ years of experience in Data Engineering, with 2-3+ years in a Lead or Staff-level role.

Proven experience owning system design and leading implementations of large-scale data platforms.

Strong hands-on expertise with Snowflake, Azure Databricks, DBT, and Python, including thousands of DBT models and data pipelines processing terabytes of data daily.

Deep understanding of data architecture, data modeling, distributed data systems, and ETL/ELT frameworks.

Extensive experience with Terraform and Infrastructure-as-Code principles.

Demonstrated experience leading cloud-to-cloud data migration projects, preferably AWS to Azure.

Strong experience with CI/CD pipelines, Git-based version control, and advanced SQL.

Strong problem-solving skills with the ability to make architectural trade-offs and technical decisions.

Proven experience managing and developing teams across different performance levels through mentoring, training, and development.

Previous experience in insurance or financial services, with knowledge of claims, policies, underwriting, and risk domains, plus strong communication skills.

Preferred Skills

Experience implementing data governance, observability, and data quality frameworks.

Strong knowledge of security and compliance standards in insurance or financial services.

Experience with real-time and streaming technologies such as Kafka, Event Hubs, and Delta Live Tables.

Familiarity with lakehouse architecture and cost/performance optimization.

Experience operating in multi-cloud or hybrid cloud environments.

Posted On: 24-09-2026

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