Why Blueberry?
At Blueberry, data is more than numbers, it’s the backbone of every decision we make. We believe in building reliable, scalable, and secure data systems that empower every team to move faster and smarter. You’ll be joining a tight-knit, high-impact tech team where your work directly shapes our products, our strategy, and our customer experience.
We’re looking for a hands-on Senior Data Engineer to lead the design, optimisation, and scaling of our Snowflake data warehouse and pipelines. You’ll own our data infrastructure end-to-end, from modelling and transformations to security and performance, ensuring our business decisions are built on a foundation of clean, accurate, and accessible data.
Note: At Blueberry, moving with purpose means showing up, connecting, and building momentum together. This role is based onsite in Kuala Lumpur, Monday to Friday, where the real magic happens.
How You’ll Make an Impact
Design, optimise, and maintain our Snowflake data warehouse and DBT transformations
Refactor legacy data models for performance and cost efficiency
Build and manage robust ETL/ELT pipelines using Python, Airbyte, AWS DMS, and AWS services
Implement data masking and security measures for safe data sharing
Develop self-service BI dashboards in Power BI and Snowflake
Partner with analysts and product owners to translate business needs into data solutions
Troubleshoot pipeline issues and resolve production incidents
Establish best practices for testing, CI/CD, and documentation
Ensure all reporting is accurate, reliable, and compliance-ready
Who We’re Hoping to Find
5+ years’ experience building and scaling data warehouses & pipelines
Deep expertise with Snowflake, DBT, AWS, and strong SQL skills
Proficient in Python for scripting and API integrations
Skilled with ELT/ETL tools like Airbyte or AWS DMS
Familiar with AWS services (Lambda, S3, IAM) and data security practices
Experience in Power BI or other BI tools
Strong communicator who can translate complex concepts for non-technical audiences
Mentor-minded, collaborative, and passionate about data quality
Extra points if you have
Experience in Financial Services, Trading, or Banking
Knowledge of risk-facing teams, LLMs, or data visualisation
Familiarity with Docker and medallion architecture