Azure Databricks Data Engineering Lead

Lingaro Group Philippines; Manila; Hybrid; PHP 1,800,000 - 3,000,000; Full time

Benefits offered by this job

Office as an option

Udemy learning platform access

Certificate training programs

Job summary

Lingaro Group Philippines is seeking an experienced Data Engineering Lead to guide a team of engineers in delivering scalable data solutions. You will mentor developers, set architecture direction, and partner with stakeholders to ensure timely, high-quality outcomes.

The role requires 8–10 years in data engineering, strong Python/SQL skills, and expertise in Azure and Databricks, ETL, data warehousing, governance, and QA. GenAI tools usage is encouraged.

Qualifications

• Bachelor's or master's in CS/IS or related field.
• Experience leading data engineering teams (8–10+ years).
• Strong Python/SQL programming and data modeling skills.
• Cloud experience with Azure and Databricks required.
• Experience with ETL, data warehousing, governance, and QA.

Responsibilities

• Lead data engineering projects and mentor the team.
• Define architecture for scalable data solutions.
• Ensure on-time, quality project delivery within scope and budget.
• Collaborate with stakeholders to translate requirements into plans.
• Promote GenAI usage to accelerate delivery and quality.
• Oversee coding standards, CI/CD, and data security practices.

Skills

Python

SQL

R/Scala

Azure

Databricks

ETL

Data Warehousing

Leadership

Data Governance

Data Quality

Data Integration

GenAI tools

Project Management

Education

Bachelor's or Master’s in Computer Science / Information Systems

Tools

Azure

Databricks

Job description

Lingaro Group Philippines is seeking an experienced Data Engineering Lead to guide a team of engineers in delivering scalable data solutions. You will mentor developers, set architecture direction, and partner with stakeholders to ensure timely, high-quality outcomes.

The role requires 8–10 years in data engineering, strong Python/SQL skills, and expertise in Azure and Databricks, ETL, data warehousing, governance, and QA. GenAI tools usage is encouraged.