Senior Data Engineer: Cloud Data Pipelines on Azure

ERNI; Philippines; Hybrid; PHP 1,800,000 - 3,200,000; Full time

Benefits offered by this job

Private HMO & insurance from day one

5-year Jubilee trip to European ERNI

13th month pay

Free training and certifications

Baby basket

Fruit basket

Snacks and coffee

Job summary

ERNI is seeking a Senior Data Engineer to design, build, and optimize large-scale data pipelines on a modern cloud‑native platform. You will partner with global stakeholders to translate requirements into reliable data products, ensuring data quality and governance across enterprise datasets.

The role focuses on Azure Databricks, Delta Lake, PySpark, and orchestration, with responsibilities spanning ingestion, transformation, and delivery of analytics assets for reporting and ML use cases.

Qualifications

• Minimum 8 years of professional data engineering experience.
• Hands-on design and delivery of enterprise-scale data pipelines and analytics‑ready datasets.
• Strong experience with Azure and Azure Databricks required.

Responsibilities

• Design, develop, and optimize automated data pipelines and data products on a cloud‑native platform.
• Partner with stakeholders to clarify requirements and translate them into data solutions.
• Monitor pipeline health, troubleshoot incidents, and drive performance improvements.

Tools

Azure Data Lake Storage

Azure Data Factory

Azure Databricks

Delta Lake

PySpark

Spark SQL

SQL

ETL/ELT development

data pipeline design

data modeling

data quality controls

production support

performance tuning

stakeholder requirements clarification

Databricks Workflows

Git

CI/CD

monitoring

cost/performance optimization

Job description

ERNI is seeking a Senior Data Engineer to design, build, and optimize large-scale data pipelines on a modern cloud‑native platform. You will partner with global stakeholders to translate requirements into reliable data products, ensuring data quality and governance across enterprise datasets.

The role focuses on Azure Databricks, Delta Lake, PySpark, and orchestration, with responsibilities spanning ingestion, transformation, and delivery of analytics assets for reporting and ML use cases.