Senior Data Engineer, Cloud & Analytics
ADEAL Systems GmbH
Build cloud, data, and analytics solutions for ADEAL Systems, taking technical ownership of architecture, data pipelines, and customer projects.
Open
Mercury is a fintech and banking software company founded in 2017 that builds financial tools for startups and small to mid-size businesses. Its platform combines business checking and savings accounts, Treasury products, business credit cards, spend management, payments, invoicing, accounting integrations, and AI-powered workflow automation in one digital experience. Mercury also provides APIs and developer tools, with features such as virtual cards and granular controls designed for teams, agencies, ecommerce brands, venture capital funds, and crypto businesses. Banking services are provided through partnerships with FDIC-insured banks.
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.
Canada
United States
California
New York
Oregon$166,600 – $208,300 / year
RemoteFull-timeSeniorEnglish RequiredAnalytics EngineerDescription
- 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
Requirements
- 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
Benefits
- 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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