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Mercury — 2017-yilda tashkil etilgan, startaplar hamda kichik va o‘rta bizneslar uchun moliyaviy vositalar yaratadigan fintech va bank dasturiy ta’minoti kompaniyasi. Uning platformasi biznes uchun joriy va jamg‘arma hisobvaraqlarini, Treasury mahsulotlarini, biznes kredit kartalarini, xarajatlarni boshqarishni, to‘lovlarni, hisob-fakturalarni, buxgalteriya tizimlari bilan integratsiyani va sun’iy intellekt asosidagi ish jarayonlarini avtomatlashtirishni yagona raqamli tajribaga birlashtiradi. Mercury, shuningdek, virtual kartalar hamda jamoalar, agentliklar, elektron tijorat brendlari, venchur kapital fondlari va kripto kompaniyalari uchun mo‘ljallangan batafsil boshqaruv imkoniyatlariga ega API va dasturchi vositalarini taqdim etadi. Bank xizmatlari FDIC tomonidan sug‘urtalangan banklar bilan hamkorlik orqali ko‘rsatiladi.
Senior Analytics Engineer at Mercury Remote United States
Join Mercury as a Senior Analytics Engineer building scalable data pipelines, dimensional data marts, and AI-native analytics foundations. The role supports agentic tools, self-service analytics, governance, and data products for a fintech business.
Tavsif
- Build scalable data pipelines and business-aligned dimensional data marts in partnership with Data Science, Engineering, Product, and Operations
- Help develop and drive adoption of agentic tools such as Mercury’s AI Data Analyst, Hermes, and dbt Agent, Ralph
- Advance self-service analytics by implementing workflows, teaching Analytics Engineering practices, and supporting peers
- Deliver the data and analytics products required to support Mercury’s bank charter
- Help shape strategies for data quality, governance, and security
- Contribute to Analytics Engineering standards, processes, and best practices
- Create shared data foundations for decision-making, automation, and measurement across Mercury
- Enable durable data products, rapid experimentation, propensity modeling, agentic workflows, and data-informed customer experiences
Talablar
- At least four years of experience in Analytics Engineering or Data Engineering
- Expert-level experience with a modern data stack, including tools such as Fivetran, Airflow, Snowflake, dbt, Omni, or Hex
- Strong SQL skills
- Professional experience using Python
- Proficiency with AI agents for accelerating analytical and engineering work
- Experience applying dimensional modeling principles and designing data systems for scale
- Ability to prioritize reusable, scalable solutions
- Track record of producing readable code, robust tests, and thorough documentation
- Banking or financial services experience is an additional qualification
- Experience with agentic development or analytics workflows is an additional qualification
- Familiarity with data governance, compliance, and security practices is an additional qualification
- Full-stack perspective and willingness to solve problems end to end is an additional qualification
Imtiyozlar
- Base salary
- Equity through stock options or restricted stock units
- Employee benefits
- Reasonable accommodations during the recruitment process for applicants with disabilities or special needs
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