Senior Analytics Engineer (Platform - Financial Analytics)

About the Team

The Finance Analytics team bridges the gap between data engineering data science and business analytics by building scalable impactful data solutions that empower Finance Accounting/Controllership and Treasury stakeholders to make data-driven decisions. We bring deep domain knowledge spanning accounting business controllership SOX compliance and internal audit - ensuring our pipelines data models and certified financial datasets meet the rigor and traceability demands of a regulated financial environment.

This role supports the data layer efforts that underpin these datasets and the controls/observability needed to keep them reliable. The team partners closely with Finance Accounting Treasury and Product Engineering to ensure financial data is complete reconciled and audit-ready - supporting core workflows like month-end close safeguarding and reporting at scale.

What You'll Be Doing:

This is a hybrid Data Engineer/Data Scientist/Business Analyst role that has the expertise to understand data flows end to end and the engineering toolkit to extract the most value out of it indirectly (building tables) or directly (solving problems delivering insights).

• Be the expert: Quickly build subject matter expertise in a specific business area and data domain. Understand the data flows from creation ingestion transformation and delivery.
  • Step into a new line of business and work with Engineering and Product partners to deliver first data pipelines and insights.
  • Communicate with engineering teams to fix data gaps for downstream data users.
  • Take initiative and accountability for fixing issues anywhere in the stack.
  • Perform reconciliation-style validation across sources (internal systems and/or external statements/vendors) identifying discrepancies and driving fixes with upstream owners.
• Examples:
• Generate business value: Interface with stakeholders on data and product teams to deliver the most commercial value from data (directly or indirectly).
  • Build curated data models that streamline ledger verification and accounting workflows helping finance teams accelerate time-to-close for new product launches.
  • Leverage deep understanding of the reconciliation engine alongside statistical and data expertise to propose engineering improvements that drive faster execution and higher match accuracy.
  • Work with PMs to tie together new x-PG and x-Product data into one holistic framework to optimize key financing product business metrics.
  • Collaborate cross-functionally with Finance/Accounting to translate requirements into durable data models and with upstream engineering teams to improve source data contracts.
• Examples:
• Focus on outcomes not tools: Use a variety of frameworks and paradigms to identify the best-fit tools to deliver value.
  • Develop new abstractions (e.g. UDFs Python packages dashboards) to support scalable data workflows/infra.
  • Stand up a framework for debugging AI skills/data apps internally enabling other non-tech stakeholders to quickly add value.
  • Use established tools with mastery (e.g. Google Sheets SQL) to quickly deliver impact when speed is top priority.
• Examples:
• Ensure financial correctness & reliability: Implement strong data quality guarantees (tests monitoring alerting SLAs) and partner with stakeholders to define "done" for financial correctness. Improve reliability and operational excellence for critical pipelines (incident response retro/action items performance tuning cost optimization).

What We Look For in You:

• Strong understanding of best practices for designing modular and reusable data models (e.g. star schemas snowflake schemas). Experience designing curated datasets for analytics/reporting with clear definitions and change management.
• Proficiency in advanced SQL techniques for data transformation querying and optimization.
• Expertise in scripting and automation with experience in Object-Oriented Programming (OOP) and building scalable frameworks.
• Strong ability to translate technical concepts into business value for cross-functional stakeholders. Proven ability to manage projects and communicate effectively across teams.
• Strong cross-functional communication skills and ability to work effectively with Finance/Accounting partners and navigate ambiguity.
• Experience building maintaining and optimizing ETL/ELT pipelines using modern tools like dbt Airflow or similar. Experience orchestrating data workflows with Airflow (DAG design scheduling patterns backfills operational ownership).
• Proficiency in building polished dashboards using tools like Looker Tableau Superset or Python visualization libraries (Matplotlib Plotly).
• Familiarity with version control (GitHub) CI/CD and modern development workflows.
• Knowledge of modern data lake/warehouse architectures (e.g. Snowflake Databricks) and transformation frameworks. Hands-on experience with Snowflake and/or Databricks in production environments.
• Track record of building for correctness and reliability: data quality frameworks monitoring/alerting incident response and stakeholder-facing SLAs.
• Ability to understand and address business challenges through analytics engineering.
• Familiarity with statistics and probability.
• Expertise in prompt engineering and design for LLMs (e.g. GPT) including creating refining and optimizing prompts to improve response accuracy relevance and performance for internal tools and use cases.
• Demonstrate the ability to responsibly use generative AI tools and copilots (e.g. LibreChat Gemini Glean) in daily workflows continuously learn as tools evolve and apply human-in-the-loop practices to deliver business-ready outputs and drive measurable improvements in efficiency cost and quality.

Nice to Haves:

• Experience with financial reconciliation controllership/accounting reporting audit/SOX-style controls or regulated environments.
• Familiarity with ledger/event-based financial models and concepts like double-entry accounting.
• Experience with streaming/event-driven systems (e.g. Kafka/Kinesis) and/or near-real-time data validation patterns.
• Experience with table replication/synchronization patterns between lakehouse and warehouse environments.
• Fintech/crypto domain experience.
• New York City location presence preferred. The role is remote-friendly but we prefer candidates who can commute to our NYC office for stakeholder meetings and project work as needed.

Job ID: P76160

What We Do

Crypto creates economic freedom by ensuring that people can participate fairly in the economy and Coinbase (NASDAQ: COIN) is on a mission to increase economic freedom for more than 1 billion people. We’re updating the century-old financial system by providing a trusted platform that makes it easy for people and institutions to engage with crypto assets including trading staking safekeeping spending and fast free global transfers. We also provide critical infrastructure for onchain activity and support builders who share our vision that onchain is the new online. And together with the crypto community we advocate for responsible rules to make the benefits of crypto available around the world.

Why Work With Us

We have the opportunity to accelerate the pace of innovation in the world by building an open financial system. Our vision is to create more economic freedom in the world to help people control their own wealth start companies have financial privacy and participate in the global economy. And to get us there we focus build and move as a team.

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