Remote Employee BPO has an outstanding opportunity for you!

• Role: Data Engineer
• Compensation: Competitive Basic Salary
• Benefits: HMO plus 2 Free Dependents, P1,500 Rice Allowance, and Night Differential, Government Mandated Benefits, SIL, Company Events, etc
• Work Schedule: 5-day work week, Monday to Friday, 10:00 p.m. to 7:00 a.m. Philippine Time
• Work Setup: Work-from-Home

We are seeking a skilled and motivated Data Engineer with hands-on experience in ETL development, Azure Data Factory (ADF), Azure Data Lake, and SQL Server Integration Services (SSIS). The ideal candidate will have hands-on experience in designing, building, and working with cloud-based solutions and maintaining scalable data pipelines that support advanced analytics, reporting, and business intelligence initiatives.

• Design and implement robust ETL/ELT pipelines using SSIS, ADF, and other Azure-based tools.
• Ingest, clean, transform, and validate large volumes of structured and semi-structured data.
• Manage and optimize data storage solutions within Azure Data Lake and other Azure services.
• Collaborate with data analysts, data scientists, and business stakeholders to understand requirements and deliver high-quality data solutions.
• Monitor, troubleshoot, and improve data pipelines to ensure data integrity and performance.
• Ensure security, privacy, and compliance with relevant data governance policies.
• Document technical solutions, data flows, and ETL processes for maintainability and transparency.

Preferred Qualifications

• Microsoft Azure certifications (e.g., DP-203: Data Engineering on Microsoft Azure).
• Experience with Python and PySpark in a data engineering context.
• Exposure to CI/CD practices in data pipeline development.
• Experience with Delta Lake and data lake house architecture.
• Knowledge of data modeling concepts and tools (e.g., star/snowflake schema).
• Familiarity with other Azure services such as Azure Synapse, Azure Functions, or Logic Apps.
• Proficiency in writing complex SQL queries and performance tuning.
• Experience working with large-scale data platforms and cloud-based data ecosystems.
• Strong understanding of data modeling, ETL best practices, and data warehousing concepts.
• Familiarity with version control systems like Git.
• Excellent problem-solving skills and attention to detail.
• Strong communication and collaboration skills.

Required Skills and Experience:

• 3+ years of experience in Data Engineering or related role.
• Strong hands-on experience with:
• SQL Server Integration Services (SSIS)
• Azure Data Factory (ADF)
• Azure Data Lake (Gen1/Gen2)
• ETL processes and frameworks