Data Engineer

Summary

Join ConnectOS, a top-rated Philippines employer and a Great Place to Work certified company, as a Data Engineer. You will design, develop, and manage data infrastructure on Google Cloud Platform (GCP), collaborating with data scientists and analysts. Responsibilities include building data pipelines, maintaining data warehouses, optimizing data solutions, and automating tasks. This role requires at least 3 years of experience in data engineering, proficiency in Python and SQL, and expertise in GCP services. Competitive salary, home-based work, comprehensive medical coverage, paid leave, and various other benefits are offered.

Requirements

• Minimum of 3 years of experience in data engineering or a similar role
• Python programming and SQL
• Strong understanding of data modeling, design, ETL processes, and data warehousing concepts
• Experience with data visualization tools (e.g., Tableau, Power BI, Looker Studio) and proficiency in dashboard development and reporting
• Experience in Google Cloud Platform (GCP) stack including: Google Cloud Storage, BigQuery, Compute Engine, Cloud Composer, Cloud Function, DataFlow, Pub/Sub
• Kubernetes
• Apache Airflow
• DataOps
• Experience in developing, deploying, and maintaining end to end data pipelines
• Experience using IDE
• Comfortable with git or other software versioning systems
• Agile methodologies experience

Responsibilities

• Design and implement scalable data pipelines, ETL processes, and data integration workflows using GCP tools and services
• Build and maintain data warehouses and data lakes on GCP, ensuring data integrity, accuracy, and security
• Work closely with data scientists, analysts, and other stakeholders to understand data needs and deliver actionable insights
• Optimize data pipelines and storage solutions for performance, cost, and reliability
• Automate data processing tasks and workflows to improve efficiency and reduce manual effort
• Monitor data systems, troubleshoot issues, and implement solutions to maintain system health and performance
• Document data architectures, processes, and best practices to ensure knowledge sharing and consistency

Preferred Qualifications

• Familiarity with machine learning and AI concepts
• Stakeholder management
• Google Cloud Professional Data Engineer certification
• Databricks
• ML Ops
• ML Flow
• Docker

Benefits

• Home-based
• Medical, Dental Coverage and Life insurance from day 1 of employment
• Paid Vacation and Sick Leave (with Quarterly Sick Leave Conversion)
• Competitive salary package and annual appraisal
• Financial Assistance Program
• Mandatory Government Benefits and 13th Month Pay
• Regular Company Events, Work Life Balance, and Career growth opportunities