Senior Analytics Engineer

About Us

We are

Ryt Bank , proudly awarded as one of the five digital banking license winners by BNM in Malaysia. Our mission is to empower the underserved and unserved segments of the population by providing innovative and accessible banking solutions. As a member of our team, you will play a

key role in shaping the future of digital banking, using AI to enhance the banking experience for Malaysians . Our team is made up of experienced digital banking and fintech innovators, excited to bring our expertise to Ryt Bank, as we continue to

drive impactful innovation . About the Role

We are seeking a

Senior Data Engineer, Analytics

to bridge the gap between data engineering and analytics, focusing on building and maintaining scalable data models while enabling stakeholders to make data-driven decisions. You will be operating with a high level of autonomy, collaborating directly with product, business partners, and peer engineering teams to align on requirements and execute effectively in a fast-paced environment. Key Responsibilities

Design, implement and maintain robust data models to support analytics, dashboards, and self-serve tools Architect and develop high quality data assets for business, analytics and regulatory reporting use cases Collaborate with stakeholders to understand business requirements and translate them to technical solutions Establish data modelling best practices, tooling, documentation and testing methodologies - ensuring models are highly maintainable and scales with complexity Lead technical design discussions and contribute to data architecture decisions - spotting opportunities to reduce complexity and cost Lead, guide and mentor team members on best practices - You will review the designs and work of engineers on the team and set a high bar for quality. What we're seeking

Strong passion for data modelling - SQL and data modelling are second nature to you Proven experience with dbt and modern data warehouse platforms (Snowflake, Redshift) - you are comfortable with general warehousing concepts Strong understanding of software engineering best practices and data engineering principles Experience implementing data quality monitoring and testing frameworks Ability to tackle complex problems from both technical and business perspectives Excellence in stakeholder communication and leading technical initiatives in a fast-paced environment Background in implementing metrics frameworks and data governance (bonus) Familiarity with AI / ML and their applications in analytics (bonus) Ability to think strategically about banking products / operations and how our underlying data models will unlock more insights and value for our customers (bonus) Language : SQL, Python Orchestration : Airflow Transformation : dbt Warehousing : Greenplum Lead critical data modelling initiatives that power company-wide analytics Shape data engineering practices and tooling decisions Mentor and grow other team members' technical capabilities Drive adoption of modern data solutions Influence data architecture and governance strategies Seniority level

Mid-Senior level Employment type

Full-time Job function

Engineering, Finance, and Information Technology Industries

Banking, IT System Data Services, and Software Development

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