Tech Lead Manager, Data Integration Platform

Title: Tech Lead Manager, Data Integration Platform Location: San Francisco, CA, USA

About the Role

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, powering analytics, experimentation, and AI-driven product experiences across Chime.

You'll partner closely with other Data Intelligence Platform squads as well as Product Engineering, Security, and Analytics teams to define integration patterns, data contracts, and SLAs that govern how data enters and leaves Chime, supporting both high-scale batch workloads and latency-sensitive real-time flows. Your leadership will directly impact how Chime ingests, exchanges, and delivers data - enabling trusted, self-serve, AI-ready data for Chimers across the company.

Chime’s data integration platform is entering its next phase. As our data ecosystem grows, we have a significant opportunity to simplify and standardize how data moves across streaming, batch, and third-party integrations. You will lead the evolution toward a unified, secure, and reliable data conveyance platform while helping advance Chime’s lakehouse architecture.

This is a manager-first, hands-on player-coach role. Your primary responsibility is leading and developing the team - setting direction and priorities, coaching engineers, and owning delivery and operational health. You will also remain technically engaged through high-leverage problems: shaping architecture, guiding designs, reviewing critical changes, and writing production code where it unlocks the team’s progress.

In this role, you can expect to

• Own the strategy and roadmap for Chime's Data Integration Platform, including ingestion pipelines, connectors, and the infrastructure that moves first-party and third-party data into and out of Chime's ecosystem.
• Stay hands-on through architecture, design and code reviews, and targeted production contributions focused on the highest-leverage platform problems, while coaching engineers and owning team execution.
• Design and evolve scalable, high-performance integration architecture that balances reliability, cost, and ease of use for both analytical and in-product data flows.
• 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 for key data flows.
• Collaborate across the Data Intelligence Platform and partner teams to define clear data contracts, schemas, and SLAs between producers, the integration layer, and consumers including external partners.
• Build tooling and automation for governance and compliance across sources and sinks (e.g., RBAC, PII protection, tokenization, lineage, and auditability), with particular attention to data leaving Chime's boundary, 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 integration pipelines and connectors your team owns.
• Stay ahead of industry trends in data integration, streaming, and ingestion/egress tooling, 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 integration or data movement systems.
• Have 3+ years of experience managing engineering teams, including hiring, performance management, and developing engineers.
• Bring hands-on coding ability and a genuine desire to remain technical while leading a team. You are comfortable writing and reviewing production code, particularly where it resolves ambiguity or unlocks the team’s progress
• Have a track record of scaling products, platforms, and operations to support rapid growth in data volume, complexity, and criticality.
• Bring 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 the data lakes/lakehouses (e.g., Iceberg) and warehouses (e.g., Snowflake) they feed and drain.
• Have 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.
• Are 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).
• Are hands-on proficient in Python (preferred) or a comparable language (e.g., Java, Scala), able to write, review, and ship production-quality code, and are fluent in SQL and performance tuning for analytical workloads.
• Have 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) especially for third-party data sharing and data crossing Chime's trust boundary and have helped design systems that meet regulatory and internal standards.
• Are deeply interested in the transformative potential of advanced AI systems and how to build AI-ready data foundations (metadata, lineage, semantic layers, and reliable data pipelines that feed them).
• Excel at building strong relationships with stakeholders across engineering, product, analytics, security, and finance, as well as external partners and vendors, and can translate between technical and business contexts.
• Demonstrate strong people leadership, with a track record of building a culture of belonging and engineering excellence.

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