Senior Data Engineer: Scalable Pipelines & Data Governance

B&M Global Services Manila; Taguig; On-site; PHP 1,200,000 - 1,800,000; Full time

Job summary

Baker McKenzie is seeking an experienced Data Engineer in Metro Manila to build robust data pipelines and data infrastructure. You will design, develop, and maintain systems for data storage, processing, and analytics, collaborating with data teams to deliver high-quality data for business insights.

You will work with modern tools like Snowflake, Kafka, Airflow, Spark, and Databricks, and help implement governance, security, and data quality measures across enterprise data assets.

Qualifications

• Bachelor's degree in computer science or related field; master's preferred.
• At least six years of data engineering experience in data management and integration.
• Proven project experience with data warehouses (Snowflake).
• Expert knowledge of Apache Kafka, Airflow, and Spark.
• Proficiency in Java, Python, and SQL; familiarity with data science tools.

Responsibilities

• Designs and develops data pipelines to extract, transform, and load data.
• Collaborates with data scientists to optimize models for data quality and governance.
• Integrates data from databases, warehouses, APIs, and external systems.
• Ensures data consistency, validation, and cleansing throughout processing.
• Optimizes pipelines and processing workflows for performance and scalability.
• Monitors systems and implements caching and indexing for faster queries.

Skills

Data pipelines

Big data

Java

Python

SQL

Education

Bachelor's degree

Master's preferred

Tools

Snowflake

Kafka

Airflow

Spark

Databricks

Job description

Baker McKenzie is seeking an experienced Data Engineer in Metro Manila to build robust data pipelines and data infrastructure. You will design, develop, and maintain systems for data storage, processing, and analytics, collaborating with data teams to deliver high-quality data for business insights.

You will work with modern tools like Snowflake, Kafka, Airflow, Spark, and Databricks, and help implement governance, security, and data quality measures across enterprise data assets.