Data Engineer

Bridgit; Manila; On-site; PHP 669,600 - 1,116,000; Full time

Benefits offered by this job

Extra Leave

Two Weeks from Anywhere

Learning and Development

Social Events

Job summary

Bridgit is looking for a Data Engineer to work in Cebu, Manila (Hybrid). The role involves designing, building, and maintaining scalable batch and streaming data pipelines using AWS + Databricks.

The ideal candidate should have 3 to 5+ years of experience along with strong skills in Python and SQL. They will ensure data quality and collaborate with team members to meet data needs. Bridgit offers extra leave, remote work opportunities, and support for learning and development.

Qualifications

• 3 to 5+ years of experience in data engineering projects.
• Strong command of NumPy, Pandas, and related libraries.
• Hands‑on experience with ETL/ELT orchestration tools.
• Familiarity with AI‑assisted development tools is a plus.

Responsibilities

• Design, develop, and optimize data pipelines using AWS + Databricks.
• Implement data models and transformations following best practices.
• Ensure data quality, reliability, and lineage through monitoring.
• Collaborate with data stakeholders to translate requirements.

Skills

Python proficiency

SQL skills

AWS + Databricks experience

Data modeling

ETL/ELT orchestration

Git for version control

Excellent communication skills

Tools

Azure Data Factory

Fabric Pipelines

Power BI

Job description

Data Engineer

Location: Cebu, Manila (Hybrid)

We’re looking for a Data Engineer with solid experience in Python, SQL, and modern lakehouse architectures in AWS + Databricks. In this role, you’ll help design, build, and maintain highly scalable batch and streaming data pipelines, optimizing performance and ensuring robust data quality across the enterprise.

What you’ll do

• Design, develop, and optimize data pipelines for both batch and streaming workloads using AWS + Databricks.
• Implement data models, transformations, and ingestion frameworks following best practices (e.g., Medallion architecture: Bronze–Silver–Gold).
• Manage and maintain ETL/ELT processes using Azure Data Factory, Fabric Pipelines, or equivalent tools.
• Develop and maintain high-performance SQL queries and analytical models for reporting and analytics.
• Ensure data quality, reliability, and lineage through testing, monitoring, and documentation.
• Collaborate with data scientists, analysts, and business stakeholders to translate requirements into scalable technical solutions.
• Manage version control, branching, and CI/CD processes using Git.
• Drive adoption of engineering best practices, including modular code design, testing, and automation.

What you’ll bring

Must-Have Skills

• 3 to 5+ years of experience in data engineering projects spanning batch and streaming data workloads.
• Strong Python proficiency, including a strong command of NumPy, Pandas, and related data-processing libraries.
• Strong SQL skills – capable of building efficient, production-grade transformations and analytical models.
• Proven experience with AWS + Databricks, particularly in Delta Lake or Lakehouse environments.
• Strong understanding of data modeling (Star/Snowflake), Medallion architecture (Bronze–Silver–Gold), and incremental/CDC design patterns.
• Hands‑on experience with ETL/ELT orchestration (Azure Data Factory, Fabric Pipelines, or equivalent).
• Proficient with Git for version control, branching strategies, and CI/CD integration – this is essential.
• Excellent communication, documentation, and stakeholder collaboration skills.

Good‑to‑Have Skills

• Familiarity with AI‑assisted development tools such as Cursor, GitHub Claude, or similar productivity‑enhancing environments.
• Exposure to Power BI, Fabric Data Warehouse, and Semantic Models (DAX).
• Knowledge of data governance, lineage, and data quality frameworks.
• Experience with data platforms built in AWS.
• Understanding of DevOps principles and cloud cost optimization for data workloads.
• Experience integrating machine learning models or LLM‑based workflows into data pipelines.

Our Culture and Benefits

• Extra Leave – Birthday leave + an additional day of paid leave for life events, celebrations, or mental health reset.
• Two Weeks from Anywhere – Employees can work remotely from a location of their choice for two weeks each year.
• Learning and Development – Employees are encouraged and empowered to engage in professional development, including internal learning initiatives.
• Social Events – A jam‑packed social scene, with events throughout the year to bring the team together.