Join global data team building the infrastructure that powers analytics and AI-driven insights across the organization. As a Data Engineer, you'll design and maintain scalable data pipelines and systems that enable product analytics, business intelligence, and AI applications in our high-growth fintech environment.
What you'll do:
Design, build, and maintain robust batch and streaming pipelines and orchestration across our modern stack (AWS, DBT, Airbyte, Airflow, Snowflake) to support AI-driven data products.
Develop and optimize data models in Snowflake, ensuring data quality, consistency, and performance at scale.
Collaborate with Product Analysts and AI specialists to implement data solutions for customer segmentation, ranking systems, and predictive models.
Partner with cros-functional teams to translate technical requirements into scalable data architecture.
Implement end-to-end observability (data quality checks, monitoring, alerting) and cost/performance optimization in Snowflake and AWS.
Requirements: 6+ years of experience as a Data Engineer or similar role.
Expert proficiency in SQL and hands-on experience with modern data warehouse platforms (Snowflake - advantage).
Strong experience building ETL/ELT pipelines using tools like DBT, Airflow, or similar orchestration frameworks.
Proficiency in Python or another programming language for data processing.
Solid understanding of data modeling techniques (dimensional modeling, Data Vault, etc).
Experience with cloud platforms, preferably AWS.
Proven ability to design and maintain reliable, scalable data systems with a strong focus on data quality.
Strong communication skills and the ability to work effectively with both technical and business stakeholders.
Experience with fintech, financial services, or cryptocurrency/blockchain - advantage.
Familiarity with real-time data processing or streaming technologies - advantage.
This position is open to all candidates.