Data Engineering Tech Lead

We're building the data foundation that will power Nimble at massive scale. We're looking for a battle-tested Data Engineering Tech Lead who has built and scaled data infrastructure at companies where the bar is exceptionally high. This is a ground-up, architect-and-build role. You'll own the entire data infrastructure layer - caching, indexing, storage architecture, scalability patterns - and set the standard for how data flows across the organization at scale.

Requirements: • 10+ years in data engineering, with significant time spent at fast-moving, high-scale tech companies. • Deep expertise in database architecture across OLTP, OLAP, NoSQL, and columnar systems, including MongoDB/Atlas, PostgreSQL, Redis, Elasticsearch, ClickHouse, and Couchbase. • Proven hands-on experience with DAG-based workflow orchestration systems such as Apache Airflow, Temporal, Prefect, Dagster, or similar - designing, scaling, and operating complex pipeline workflows in production. • Hands-on with cloud-native data infrastructure (AWS/GCP/Azure) and deep experience with data lake platforms - Databricks, Snowflake, BigQuery, or similar - including streaming and batch pipelines at scale. • Hands-on experience with event-driven architectures and event sourcing patterns (e.g., Kafka, Kinesis, or similar), with strong command of distributed systems principles - partitioning, replication, consistency trade-offs. Who You Are • Exceptional communicator - able to lead cross-functional design and implementation, work fluidly with engineers, product managers, and senior stakeholders, and drive execution across organizational boundaries. • A true people person - thrives working alongside talented teams, leaves ego at the door, and brings a can-do attitude to every challenge.