(URGENT) Data Engineer – Data Integration & ETL Solutions | Manila Onsite | ATCP-1443903-S425759

Job Description: Databricks Data Engineer – Data Pipelines & ETL

Location: Manila, Philippines
Work Setup: Onsite
Work Shift: Shifting Schedule
Experience: Minimum 2 Years
Employment Type: Full-Time
Salary: Confidential – to be discussed during the job offer

Job Summary

We are looking for a skilled Databricks Data Engineer to design, develop, and maintain scalable data pipelines and data processing solutions. The ideal candidate will have hands-on experience with the Databricks Unified Data Analytics Platform, Apache Spark, and ETL/ELT processes.

The successful candidate will work with cross-functional teams to build reliable data workflows, transform raw data into curated datasets, optimize query performance, and maintain high standards of data quality, security, and operational efficiency.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines using Databricks and Apache Spark.

• Build and optimize batch and streaming data-processing workflows to support business requirements.

• Implement ETL/ELT processes to extract, transform, validate, and load data across multiple systems.

• Transform raw data into structured, curated, and analytics-ready datasets.

• Design and implement data warehouse structures, including Snowflake schemas, fact tables, and dimension tables.

• Write, optimize, and troubleshoot SQL queries to improve processing speed and efficiency.

• Monitor data pipelines and identify opportunities to improve reliability, scalability, and performance.

• Implement data access controls, permissions, and governance policies using Unity Catalog.

• Ensure data accuracy, consistency, completeness, and quality throughout the data lifecycle.

• Collaborate with business stakeholders, analysts, and technical teams to gather requirements and translate them into technical specifications.

• Troubleshoot data pipeline failures, data quality issues, and performance bottlenecks.

• Document data architectures, workflows, transformation logic, and operational procedures.

• Participate actively in team discussions, knowledge-sharing sessions, and continuous improvement initiatives.

• Stay updated on emerging data engineering technologies, tools, and industry best practices.

Required Skills and Qualifications

• Minimum 2 years of hands-on experience with the Databricks Unified Data Analytics Platform.

• Strong understanding of data pipeline architecture and implementation.

• Practical experience with Apache Spark and distributed data processing.

• Experience developing and maintaining ETL/ELT pipelines.

• Strong SQL skills, including query optimization and data transformation.

• Knowledge of data warehouse concepts, including Snowflake schemas, fact tables, and dimension tables.

• Experience with batch and streaming data workflows.

• Understanding of data governance, access controls, and permissions using Unity Catalog.

• Familiarity with cloud-based data platforms and distributed computing environments.

• Strong analytical, troubleshooting, and problem-solving skills.

• Ability to collaborate with cross-functional teams and work independently.

Work Requirements

• Willingness to work onsite at the Manila office.

• Availability to work on a shifting schedule.

• Ability to communicate effectively with team members and stakeholders.

Benefits and Compensation

Compensation details will be discussed during the job offer.

Recruitment Process

1. Initial CV screening with the CV Reviewer.

2. Candidate validation and further CV screening through Workday, including the HRI toolkit, FCV, and CV.

3. Submission for client review.

Pre-Screening Questions

1. How many years of relevant hands-on experience do you have with the Databricks Unified Data Analytics Platform?

2. What was your last drawn salary?

3. What is your expected salary?

4. Are you amenable to working onsite on a shifting schedule in Manila?

Candidate Submission Requirements

Candidates should submit their latest CV in PDF format. Recruiters should include screening notes covering Databricks experience, relevant data engineering projects, technical skills, salary details, and availability.

Ideal Candidate: A data engineering professional with strong Databricks, Spark, SQL, and ETL/ELT skills who can build scalable data pipelines and deliver reliable, high-quality datasets.