2 дня назад
Engineering Manager, Data Platform (Fintech)
199 000 - 275 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Engineering Manager, Data Platform (Fintech): Leading the Data Storage team in building and operating reliable, scalable, and secure online and analytical data stores and low-latency serving layers with an accent on data architecture, governance, and AI-ready foundations. Focus on defining storage strategies and SLAs, scaling batch and real-time workloads, and developing engineers while maintaining operational excellence.
Location: San Francisco, CA, USA; hybrid work with four days a week in the office and Fridays from home for employees near an office.
Salary: $199,000–$275,000 annual base salary, plus bonus, equity, and benefits.
Company
is a financial technology company providing user-friendly banking services and financial tools to help members make financial progress.
What you will do
- Lead the Data Storage team and own the strategy and roadmap for online and analytical data stores, including Snowflake and data lake platforms.
- Design scalable, high-performance storage architecture for analytical and latency-sensitive product workloads.
- Define data access patterns, schemas, data contracts, SLAs, partitioning, clustering, indexing, caching, and serving layers.
- Build governance and compliance tooling covering RBAC, PII protection, tokenization, lineage, and auditability.
- Establish operational practices including on-call, incident management, postmortems, and SLOs.
- Hire, coach, and develop engineers while raising standards for technical excellence and operational reliability.
Requirements
- 8+ years of experience in high-scale, high-reliability software development focused on platforms, infrastructure, and data storage systems.
- 3+ years of experience managing engineering teams, including hiring, performance management, and engineer development.
- Deep experience with data lakes, lakehouses such as Iceberg, data warehouses such as Snowflake, online and offline stores, and batch and real-time streaming systems.
- Expertise in scalable, secure, and cost-efficient data architecture, including schema design, data modeling, and partitioning.
- Experience with technologies such as Spark, Flink, Kafka, Airflow, Kubernetes, Python, Java, Scala, SQL, and cloud data ecosystems including AWS, GCP, or Azure.
- Knowledge of data governance, security, compliance, RBAC, PII handling, auditability, and AI-ready data foundations.
Nice to have
- Experience introducing modern data storage, lakehouse, and AI/ML-ready data technologies.
- Experience scaling platforms and operations through rapid growth in data volume, complexity, and criticality.
Culture & Benefits
- In-office and fully remote programs are available depending on location and eligibility.
- Comprehensive health, financial, and wellbeing benefits, including backup care and commuter subsidies for eligible employees.
- Generous vacation policy, company-wide paid days off, and paid parental leave.
- Annual wellness stipend and family planning reimbursement.
- Bonus, competitive equity package, and opportunities to work on financial technology used by millions of members.
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