Data Engineer: Scalable Lakehouse Pipelines & AI

Bridgit; Pasig; Remote; PHP 3,717,000 - 5,576,000; Full time

Benefits offered by this job

Extra Leave

Two Weeks from Anywhere

Learning and Development

Social Events

Job summary

Bridgit is a leading fintech data team seeking a Data Engineer to design and maintain scalable data pipelines on AWS with Databricks. You will implement data models, maintain data quality, and collaborate with analysts and data scientists to deliver robust data solutions.

You will work with technologies like Delta Lake, Medallion architecture, and modern lakehouse tools, while participating in CI/CD practices and Git workflows to drive scalable data engineering across the enterprise.

Qualifications

• 3–5 years of experience in data engineering for batch and streaming workloads.
• Strong Python with NumPy/Pandas and production-grade SQL.
• Experience with AWS and Databricks in Delta Lake / Lakehouse environments.
• Knowledge of data modeling (Star/Snowflake) and Medallion architecture.

Responsibilities

• Design, build, and optimize data pipelines for batch and streaming workloads on AWS.
• Develop data models and ingestion frameworks following Medallion pattern.
• Ensure data quality, lineage, testing, and documentation.
• Collaborate with analysts, data scientists, and stakeholders.

Skills

Python

SQL

Databricks

AWS

Data Modeling

ETL/ELT

Git & CI/CD

Delta Lake

Medallion Architecture

Batch & Streaming

Tools

Azure Data Factory

Fabric Pipelines

Delta Lake

Job description

Bridgit is a leading fintech data team seeking a Data Engineer to design and maintain scalable data pipelines on AWS with Databricks. You will implement data models, maintain data quality, and collaborate with analysts and data scientists to deliver robust data solutions.

You will work with technologies like Delta Lake, Medallion architecture, and modern lakehouse tools, while participating in CI/CD practices and Git workflows to drive scalable data engineering across the enterprise.