Staff Data Engineer

Staff Data Engineer The Data team is responsible for designing and operating the data infrastructure that powers insight, reporting, analytics, and machine learning across the business. As a Staff Data Engineer you will lead architectural initiatives, mentor others, and build high‑scale systems that impact the entire organization. You will partner closely with product, analytics, ML, finance, operations, and engineering teams to move, transform, and model data reliably, with observability, resilience, and agility. Location requirement: This role is required to be in person twice a week at either our San Francisco, CA or New York City, NY office. Responsibilities Lead the architecture, design, and implementation of data infrastructure and pipelines, spanning both batch and real‑time / streaming workloads Build and maintain scalable, efficient, and reliable ETL/ELT pipelines using languages and frameworks such as Python, SQL, Spark, Flink, Beam, or equivalents Work on real‑time or near‑real‑time data solutions (e.g. CDC, streaming, micro‑batch) for use cases that require timely data Partner with data scientists, ML engineers, analysts, and product teams to understand data requirements, define SLAs, and deliver coherent data products that others can self‑serve Establish data quality, validation, observability, and monitoring frameworks (data auditing, alerting, anomaly detection, data lineage) Investigate and resolve complex production issues: root cause analysis, performance bottlenecks, data integrity, fault tolerance Mentor and guide more junior and mid‑level data engineers: lead code reviews, design reviews, and best‑practice evangelism Stay up to date on new tools, technologies, and patterns in the data and cloud space, bringing proposals and proof‑of‑concepts when appropriate Document data flows, data dictionaries, architecture patterns, and operational runbooks Minimum Qualifications 8+ years of experience in data engineering (or similar) roles Strong experience in ETL/ELT pipeline design, implementation, and optimization Deep expertise in Python and SQL writing production‑quality, maintainable, testable code Experience with large‑scale data warehouses (e.g. Databricks, BigQuery, Snowflake) Solid grounding in software engineering fundamentals, data structures, and systems thinking Hands‑on experience in data modeling (dimensional modeling, normalization, schema design) Experience building systems with real‑time or streaming data (e.g. Kafka, Kinesis, Flink, Spark Streaming), and familiarity with CDC frameworks Experience with orchestration / workflow frameworks (e.g. Airflow) Familiarity with data governance, lineage, metadata, cataloging, and data quality practices Strong cross‑functional communication skills; ability to translate between technical and non‑technical stakeholders Proven experience in mentoring, leading design discussions, and influencing data‑engineering best practices across teams Preferred Qualifications Experience with crypto, financial services, trading, markets, or exchange systems Experience with blockchain, crypto, Web3 data — e.g. blocks, transactions, contract calls, token transfers, UTXO/account models, on‑chain indexing, chain APIs, etc. Experience with infrastructure as code, containerization, and CI/CD pipelines Hands‑on experience managing and optimizing Databricks on AWS Benefits The compensation and benefits package for this role includes: Competitive starting pay A discretionary annual bonus Long‑term incentive in the form of a new hire equity grant Comprehensive health plans 401(k) with company matching Paid parental leave Flexible time off Salary Range: The base salary range for this role is between $168,000 - $240,000 in the State of New York, the State of California and the State of Washington. This range is not inclusive of our discretionary bonus or equity package. In the United States, we offer a hybrid work approach at our hub offices, balancing the benefits of in‑person collaboration with the flexibility of remote work. Expectations may vary by location and role, so candidates are encouraged to connect with their recruiter to learn more about the specific policy for the role. Employees who do not live near one of our hubs are part of our remote workforce. Equal Employment Opportunity Statement At Gemini, we strive to build diverse teams that reflect the people we want to empower through our products, and we are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. Equal Opportunity is the Law, and Gemini is proud to be an equal opportunity workplace. If you have a specific need that requires accommodation, please let a member of the People team know. #J-18808-Ljbffr