We are looking for a seasoned Data Engineer to join our growing team. Requirements - 4+ years of experience in Data Engineering. - Proven experience building and optimizing scalable ETL/data pipelines, preferably on Azure Databricks - Experience with Azure Data Factory, Databricks, and PySpark - Solid experience integrating multiple data sources into data lakehouse / data warehouse architectures - Strong SQL skills, including designing data models and SQL Warehouse views - Experience translating business requirements into scalable and reliable data solutions/products - Experience working with cloud-based data platforms (preferably Azure) - Strong problem-solving skills with the ability to troubleshoot and optimize data pipelines - Understanding of data quality, performance optimization, and reliability best practices - Experience working in cross-functional teams and delivering data solutions in a timely manner Responsibilities - Design, build, and optimize scalable ETL/data pipelines on Azure Databricks - Automate data workflows using Azure Data Factory, Databricks, PySpark, and related Azure services - Integrate diverse data sources into data lakehouse and data warehouse solutions to enable advanced analytics - Design SQL Warehouse views and data models for downstream consumption and analytics use cases - Translate complex business requirements into scalable, reliable data products - Enhance, troubleshoot, and maintain cloud‑based data pipelines to ensure performance, reliability, and data quality - Collaborate with cross‑functional teams and contribute to timely delivery of data solutions What we offer - Flexible work arrangements. - 20 working days per year as Non-Operational Allowance for personal recreation, fully compensated. - Collaborative and supportive team culture. - Truly competitive salary. - Supportive HR and management team.

• You’ll be joining our pricing and underwriting domain to bridge the gap between machine learning/data science and engineering. • You will help build, publish, and maintain our complex data products and pipelines, key elements that have a significant impact on the company’s growth. • Shaping the architecture of data products designed for data analytics and data science specifically focusing on use cases like forecasting, feature engineering, customer behaviour, and integration of new data sources. • Leading the way in data transformation by setting up best practices in areas like Data modelling, performance optimisation, Data Governance etc, ensuring that the data used within Prima is consistent, available and reliable. • Build reusable technology that enables teams to ingest, store, transform, and serve their own data products. • Engaging with data scientists and machine learning engineers to explore the product landscape and refine data requirements for enhanced data infrastructure. • Embrace continuous learning and experimentation to stay updated on emerging technologies, from testing open source tools to engaging in community-building activities like Meetups. Your passion for staying at the forefront of the field will drive your journey.

• Shaping the architecture of data products designed for data analytics and data science specifically focusing on use cases like forecasting, feature engineering, customer behaviour, and integration of new data sources. • Leading the way in data transformation by setting up best practices in areas like Data modelling, performance optimisation, Data Governance etc, ensuring that the data used within Prima is consistent, available and reliable. • Build reusable technology that enables teams to ingest, store, transform, and serve their own data products. • Engaging with data scientists and machine learning engineers to explore the product landscape and refine data requirements for enhanced data infrastructure. • Embrace continuous learning and experimentation to stay updated on emerging technologies, from testing open source tools to engaging in community-building activities like Meetups. Your passion for staying at the forefront of the field will drive your journey.

Role Description At Umpisa Inc., our mission is to make the Philippines be known globally as a tech hub.  Umpisa Inc. is a progressive technology services company that partners with select industries, clients and people to work on pioneering and industry-changing solutions via digital transformation, modern software development and venture building. We create a set of world-class and impactful products and solutions to help organizations and individuals live better lives. We offer demanding, challenging and rewarding careers in software development, product development, emerging technologies, and more for the right candidates. Essential Skills: - Aligns with our values: Excellence, Integrity, Professionalism, People Success, Customer Success, Fun, Innovation and Diversity - Strong communication skills - Strong problem solving and analytical skills - Excellent problem-solving ability - Would like to work as part of a self-organizing Scrum team in a scaled agile framework - Must be a self-starter and loves to collaborate with the team and client Job Summary We are seeking a talented and experienced Data Engineer specializing in Google Cloud Platform (GCP) ETL tools to join our team. As a Data Engineer you will be instrumental in designing, implementing, and maintaining scalable data pipelines and systems leveraging GCP's suite of ETL tools. Responsibilities - Design, develop, and maintain scalable data pipelines using GCP ETL tools like Cloud Dataflow, Dataprep, or Dataproc - Collaborate with cross-functional teams to understand data requirements and implement solutions using GCP services to support data-driven initiatives - Optimize data models and architecture for performance and reliability within GCP - Build and maintain data warehouses, data lakes, and other data storage solutions on Google Cloud Platform - Ensure data quality, integrity, and security across various datasets within GCP - Identify and resolve performance bottlenecks in data infrastructure specifically related to GCP ETL tools - Work closely with data scientists, analysts, and other stakeholders to support their data needs within the GCP ecosystem - Stay updated with the latest GCP technologies and trends in data engineering and implement best practices