Key Responsibilities
Tabby is looking for a Senior Data Engineer to help build and evolve its core data platform, combining modern data warehouse capabilities with internal data services such as a Feature Store. You will work across DWH, streaming, and data services domains to power analytics, ML, and operational use cases across the company.
You will join a high-impact, high-growth environment and collaborate with world-class engineers, analysts, and ML teams to design and deliver scalable data solutions that are deeply integrated into Tabby's products and internal tools.
What you’ll bring
3–5+ years of experience as a Data Engineer, ML Engineer, or Backend Engineer working on data-intensive systems.
Proven experience in DWH development and maintenance for business users, analysts, and ML engineers.
Strong background in designing and operating high-load, scalable data processing and storage systems.
Solid understanding of data architecture patterns such as Kimball, Inmon, Medallion, and Data Mesh.
Hands-on experience with data modeling concepts: SCD forms, normal forms, star schema, Data Vault.
Proficiency in Python following best practices for clean, testable, and maintainable code.
Advanced SQL skills and best practices for working with large datasets and complex transformations.
Familiarity with system design best practices for distributed data platforms and services.
Experience with modern data stack tools such as Airflow, dbt, BigQuery, ClickHouse, PostgreSQL, Docker, GitLab CI/CD, and Google Cloud Platform.
Experience with event-driven systems and streaming pipelines, including tools like Debezium and message brokers/queues.
Strong communication skills in English (B2 level or higher) and the ability to work independently in a remote setup.
What you’ll bring:
What you’ll bring:
Design, build, and maintain Tabby’s corporate data warehouse to support business users, analysts, and ML engineers.
Develop and evolve internal data services such as a Feature Store and other high-impact data products.
Build and operate robust EL/ELT/ETL pipelines for both batch and streaming use cases.
Integrate new tools and practices for data processing, storage, governance, and data quality across the platform.
Implement and maintain reliable data synchronization between internal and external systems.
Design and support high-load, scalable data processing and storage solutions, ensuring performance and reliability.
Contribute to the architecture of the data platform, including technology choices and system design decisions.
Optimize infrastructure and data workflows with a focus on cost efficiency in the cloud.
Collaborate closely with analytics, risk, and ML teams to understand data needs and deliver high-quality datasets and services.
Nice to have
Experience with REST and gRPC APIs as well as message brokers and queues for integrating data services.
Experience with modern systems of data storage: relational, MPP, and NoSQL databases.
Hands-on experience with Google Cloud Platform and its data services.
GO development experience for building high-performance data services.
What we offer:
Work alongside a high-performing, international engineering team in a global fintech unicorn
Stock options (ESOP) in a fast-scaling, pre-IPO company
Health Insurance
Competitive salary and other bonuses
DETAILS TO REGISTER FOR THIS JOB:
Send your updated ATS-compliant CV:https://tabby.pinpointhq.com/en/postings/917e5e62-8412-4ec1-b863-e8be0c29e138
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