Engineering Manager, Data Platform San Francisco, CA, USA

As an Engineering Manager on Chime’s Data Platform, leading the Data Storage team, you will own the group that manages Chime’s online and analytical data stores and low-latency metric serving layer. Your team will be responsible for building and operating reliable, scalable, and secure storage foundations that power analytics, experimentation, and AI-driven product experiences across Chime. You’ll partner closely with other Data Platform squads as well as Product Engineering, Security, and Analytics teams to define storage strategies, data contracts, and SLAs that support both high-scale batch workloads and latency-sensitive online use cases. Your leadership will directly impact how Chime stores, governs, and serves data - enabling trusted, self-serve, AI-ready data for Chimers across the company. This role is not just about running infrastructure - it’s about setting a vision for the future of data storage at Chime, fostering a culture of technical excellence, and growing a high-performing team that can evolve our architecture as the business and our data scale. The base salary offered for this role and level of experience will begin at $199,000 and up to $275,000. Full-time employees are also eligible for a bonus, competitive equity package, and benefits. The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience. In this role, you can expect to Own the strategy and roadmap for Chime’s Data Storage Platform, including Snowflake, data lake and online data stores for low-latency access. Design and evolve scalable, high-performance storage architecture that balance reliability, cost, and ease of use for both analytical and in-product workloads. Ensure performant and secure data access by defining and enforcing access patterns, partitioning and clustering strategies, indexing, and caching and serving layers for key datasets and metrics. Collaborate across Data Platform and partner teams to define clear data contracts, schemas, and SLAs between producers, storage, and consumers. Build tooling and automation for governance and compliance across sinks (e.g., RBAC, PII protection, tokenization, lineage, and auditability) in partnership with Security, Risk, and Compliance. Manage and grow a team of engineers, setting clear expectations, providing coaching and feedback, and raising the bar on engineering quality and operational excellence. Establish strong operational practices, including on‑call, incident management, postmortems, and SLOs for the storage and serving layers your team owns. Stay ahead of industry trends in data storage, lakehouse architectures, and AI/ML‑ready data systems, and thoughtfully introduce technologies that improve our platform’s capabilities. To thrive in this role, you have 8+ years of experience in high-scale, high-reliability software development, with a focus on platforms, infrastructure, and data storage systems. 3+ years of experience managing engineering teams, including hiring, performance management, and developing engineers. A track record of scaling products, platforms, and operations to support rapid growth in data volume, complexity, and criticality. Deep experience with data infrastructure components, such as data lakes and lakehouses (e.g., Iceberg), data warehouses (e.g., Snowflake), online and offline data stores, and both batch and real‑time streaming systems. Proven expertise in system and data architecture for scalable, secure, and cost‑efficient data platforms, including schema design, data modeling, and partitioning strategies. Comfortable working with modern data and infrastructure technologies, such as Spark, Flink, Kafka, Airflow, Kubernetes, and similar tools. Proficient in Python or similar languages (e.g., Java, Scala) and familiar with SQL and performance tuning for analytical workloads. Extensive experience in cloud‑based data ecosystems, such as AWS (S3, DynamoDB, Redshift, Snowflake, EMR), GCP (BigQuery, Dataflow), or Azure equivalents. Understanding of data governance, security, and compliance best practices (e.g., RBAC, PII handling, auditability) and experience designing systems that meet regulatory and internal standards. Deep interest in the transformative potential of advanced AI systems and how to build AI‑ready data foundations (metadata, lineage, semantic layers, feature and metric serving). Excellent at building strong relationships with stakeholders across engineering, product, analytics, security, and finance, and able to translate between technical and business contexts. Demonstrated strong people leadership, with a track record of building a culture of belonging and engineering excellence. Chime is proud to be an Equal Opportunity Employer. We consider qualified applicants without regard to race, color, ancestry, religion, sex, national origin, sexual orientation, gender identity, age, marital or family status, disability, genetic information, veteran status, or any other legally protected basis under provincial, federal, state, and local laws, regulations, or ordinances. We will also consider qualified applicants with criminal histories in a manner consistent with the requirements of state and local laws, including the San Francisco Fair Chance Ordinance, Cook County Ordinance, NYC Fair Chance Act, and the LA City Fair Chance Ordinance, and consistent with Canadian provincial and federal laws. If you have a disability or special need that requires accommodation during any stage of the application process, please contact: View email address on click.appcast.io. #J-18808-Ljbffr Chime