engineering
Posted 1 weeks agoData Engineering Manager
(united States), United StatesRemote
Responsibilities
- RESPONSIBILITIES - Lead and develop a team of data engineers, driving execution, operational excellence, and long-term growth of the data engineering discipline - Own the reliability, scalability, and evolution of Kin’s data platform infrastructure and lakehouse environment within Databricks - Design and optimize batch, streaming, and event-driven data pipelines using technologies such as PySpark, Databricks, SQLMesh, Kafka, and Fivetran - Establish engineering standards for testing, observability, CI/CD,
- Deliver more - We build efficiency into everything we do.
Requirements
- QUICK SUMMARY Lead the evolution of Kin’s modern data platform—owning scalable pipelines, reliable lakehouse infrastructure, and the systems that power analytics, AI, and operational decision-making across the business.
- THE OPPORTUNITY We’re looking for a Data Engineering Manager to help scale the data platform that powers Kin’s analytics, operational decision-making, and machine learning capabilities.
- experience in data engineering, platform engineering, or infrastructure-focused data roles, including
- experience managing and developing data engineering teams - Hands-on
- experience building and operating modern data platforms using technologies such as Databricks, Snowflake, BigQuery, or similar lakehouse and warehouse ecosystems -
- Experience designing and maintaining scalable batch, streaming, and event-driven data pipelines using tools such as PySpark, SQLMesh, Kafka, Fivetran, or Databricks Jobs -
- Experience implementing CI/CD, automated testing, monitoring, and observability practices for data infrastructure and pipelines -
- Experience managing infrastructure-as-code and GitOps workflows using tools such as Terraform - Ability to partner effectively across technical and non-technical teams while navigating ambiguity, operational tradeoffs, and competing priorities -
- Experience leading teams through complex platform migrations, architectural evolution, or operational scaling initiatives Bonus - Exposure to AI/ML workflows, predictive analytics systems, or MLOps integration patterns -
- Experience operating in organizations where data engineering and analytics engineering are distinct but closely aligned functions HOW WE HIRE We believe a great hiring
- While our recruiting team uses AI tools for efficiency, resumes are still screened by Kin’s in-house recruiters, and candidate evaluations and hiring decisions are made by recruiters and hiring teams.