Senior Data Engineer (Python,BQ)

Who we are You will join the OneMIS stream, responsible for management, regulatory & risk reporting, and advanced analytics. Our mission includes enhancing data quality via KPIs and migrating data platforms to modern, cloud-native ecosystems. We operate in an agile environment, committed to responsible data practices.

We are looking for a Senior Data Engineer to design and deliver scalable data pipelines and high performance analytical solutions using SQL/Big. Query, Spark/Py. Spark, and Python on Google Cloud. This role focuses on building reliable, cloud native data products that enable advanced reporting, analytics, and decision making across the organization.

What you'll be doing Build scalable data pipelines: Design and deliver batch and real-time ETL/ELT pipelines across cloud environments to support analytics and reporting Develop SQL and Big. Query solutions: Write and optimize advanced SQL transformations and build performant, cost‑efficient Big. Query data models Develop Python workflows: Implement scalable data processing solutions using Python and Py.

Spark, ensuring maintainable and high‑quality code Design data models and ensure quality: Build robust data models and apply validation practices to maintain accuracy and reliability Build cloud‑native data solutions: Use GCP services such as Big. Query, Dataflow, Cloud Composer, Pub/Sub, and GCS to build and operate modern data platforms Optimize performance and reliability: Troubleshoot complex pipeline issues and continuously improve compute, storage, and processing performance Collaborate using strong engineering practices: Work with engineering, analytics, and business teams while contributing to CI/CD, code reviews, and testing standards What You'll Bring Along University degree in computer science or a comparable qualification At least 5 years of experience as a Data Engineer, building scalable data pipelines and working with cloud-based data ecosystems Strong expertise in SQL and hands‑on experience building performant datasets in Big.

Query (or similar cloud data warehouses) Proven experience with Python and Py. Spark for scalable data processing in distributed environments Solid understanding of data modeling, ELT/ETL patterns, and data quality best practices Experience with Google Cloud Platform, particularly Big. Query, Dataflow, Cloud Composer, GCS, or equivalent cloud data services Hands‑on experience building scalable data pipelines (batch and near real‑time) in a cloud‑native environment Proficiency with version control, CI/CD pipelines, and automated testing frameworks Ability to troubleshoot and optimize performance across compute, storage, and processing layers Nice to have: Experience with Infrastructure as Code (Terraform, Ansible, Chef) Knowledge of shell scripting Experience in financial services or regulated environments