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Salary: USD 199,000 - 275,000 / annual
Chime is seeking a Tech Lead Manager to lead the Data Integration Platform team, responsible for building and operating the infrastructure for ingress and egress of first-party and third-party data across Chime's ecosystem. This is a manager-first, hands-on player-coach role where you will own the strategy and roadmap for data integration pipelines, connectors, and infrastructure that move data between Chime's internal systems and external partners, vendors, and data providers.
You will partner closely with Data Intelligence Platform squads, Product Engineering, Security, and Analytics teams to define integration patterns, data contracts, and SLAs governing how data enters and leaves Chime. Your leadership will directly impact how Chime ingests, exchanges, and delivers data—enabling trusted, self-serve, AI-ready data across the company. The platform is entering its next phase, with significant opportunity to simplify and standardize data movement across streaming, batch, and third-party integrations while advancing Chime's lakehouse architecture.
Key responsibilities include owning the strategy and roadmap for the Data Integration Platform; staying hands-on through architecture, design and code reviews, and targeted production contributions on high-leverage problems while coaching engineers and owning team execution; designing and evolving scalable, high-performance integration architecture balancing reliability, cost, and ease of use; building and operating reliable connectors and pipelines for diverse sources and sinks across APIs, event streams, file transfers, and change-data-capture; ensuring performant and secure data movement by defining ingress/egress patterns, throughput and latency targets, schema evolution, and error handling; collaborating across teams to define clear data contracts, schemas, and SLAs between producers, the integration layer, and consumers including external partners; building tooling and automation for governance and compliance (RBAC, PII protection, tokenization, lineage, auditability) with particular attention to data leaving Chime's boundary; managing and growing a team of engineers with clear expectations, coaching, and feedback; establishing strong operational practices including on-call, incident management, postmortems, and SLOs; and staying ahead of industry trends in data integration and thoughtfully introducing technologies that improve platform capabilities.
Chime is a financial technology company (not a bank) that empowers members to take control of their finances through user-friendly tools and intuitive platforms. The company operates with an owner's mindset, values bold thinking and risk-taking, and maintains a deeply entrepreneurial culture.
REQUIREMENTS:
- 8+ years of experience in high-scale, high-reliability software development, with focus on platforms, infrastructure, and data integration or data movement systems
- 3+ years of experience managing engineering teams, including hiring, performance management, and developing engineers
- Hands-on coding ability and genuine desire to remain technical while leading; comfortable writing and reviewing production code, particularly where it resolves ambiguity or unlocks team progress
- Track record of scaling products, platforms, and operations to support rapid growth in data volume, complexity, and criticality
- Deep experience with data integration and movement components: ingestion and CDC pipelines, connector frameworks, event streaming, API- and file-based (e.g., SFTP) data exchange, data lakes/lakehouses (e.g., Iceberg), and warehouses (e.g., Snowflake)
- Proven expertise in system and data architecture for scalable, secure, and cost-efficient data platforms, including schema design, data contracts, and schema-evolution strategies across system boundaries
- Hands-on proficiency with modern data and infrastructure technologies: Kafka, Flink, Spark, Airflow, Kubernetes, and connector/ingestion tooling (e.g., Debezium, Fivetran/Airbyte-style frameworks)
- Hands-on proficiency in Python (preferred) or comparable language (Java, Scala); able to write, review, and ship production-quality code; fluent in SQL and performance tuning for analytical workloads
- Extensive experience in cloud-based data ecosystems: AWS (S3, DynamoDB, Redshift, Snowflake, EMR), GCP (BigQuery, Dataflow), or Azure equivalents
- Understanding of data governance, security, and compliance best practices (RBAC, PII handling, auditability), especially for third-party data sharing and data crossing trust boundaries; experience designing systems meeting regulatory and internal standards
- Deep interest in transformative potential of advanced AI systems and building AI-ready data foundations (metadata, lineage, semantic layers, reliable data pipelines)
- Ability to build strong relationships with stakeholders across engineering, product, analytics, security, finance, and external partners; can translate between technical and business contexts
- Strong people leadership with track record of building culture of belonging and engineering excellence
