As a Tech Lead Manager on Chime's Data Intelligence Platform, leading the Data Integration Platform team, you will own the group that builds and operates the platform and infrastructure for the ingress and egress of first-party and third-party data into and out of Chime's ecosystem.
Your team will be responsible for building and operating reliable, scalable, and secure integration pipelines and connectors that move data between Chime's internal systems and external partners, vendors, and data providers.
This is a manager-first, hands-on player-coach role.
Responsibilities
Own the strategy and roadmap for Chime's Data Integration Platform, including ingestion pipelines, connectors, and the infrastructure
Stay hands-on through architecture, design and code reviews, and targeted production contributions
Design and evolve scalable, high-performance integration architecture
Build and operate reliable connectors and pipelines for diverse sources and sinks across APIs, event streams, file transfers, and change-data-capture
Ensure performant and secure data movement by defining ingress/egress patterns, throughput and latency targets, schema evolution, and error handling / replay
Collaborate across the Data Intelligence Platform and partner teams to define clear data contracts, schemas, and SLAs
Build tooling and automation for governance and compliance (e.g., RBAC, PII protection, tokenization, lineage, and auditability)
Manage and grow a team of engineers
Establish strong operational practices, including on-call, incident management, postmortems, and SLOs
Stay ahead of industry trends in data integration, streaming, and ingestion/egress tooling
Requirements
8+ years of experience in high-scale, high-reliability software development, with a 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 a genuine desire to remain technical while leading a team
Track record of scaling products, platforms, and operations
Deep experience with data integration and movement components, such as ingestion and CDC pipelines, connector frameworks, event streaming, and API- and file-based (e.g., SFTP) data exchange alongside data lakes/lakehouses (e.g., Iceberg) and warehouses (e.g., Snowflake)
Expertise in system and data architecture for scalable, secure, and cost-efficient data platforms
Comfortable working with modern data and infrastructure technologies, such as Kafka, Flink, Spark, Airflow, Kubernetes, and connector/ingestion tooling (e.g., Debezium, Fivetran/Airbyte-style frameworks)
Hands-on proficient in Python (preferred) or a comparable language (e.g., Java, Scala), fluent in SQL and performance tuning
Extensive experience in cloud-based data ecosystems, such as AWS (S3, DynamoDB, Redshift, Snowflake, EMR), GCP (BigQuery, Dataflow), or Azure equivalents
Understand data governance, security, and compliance best practices (e.g., RBAC, PII handling, auditability)