Cribl is looking for a Manager, Data Engineering to lead and grow their Data Engineering function, building infrastructure that fuels analytics, enables self-service, and scales with Cribl's hyper-growth. The role aims to shape the future of Cribl's data landscape by managing a team, setting direction for the data stack, and partnering with other departments to deliver resilient pipelines and high-quality data products.
Requirements
- Experience with DevOps principles, monitoring, and automation for data infrastructure and deep knowledge of data modeling techniques and programing fundamentals (Python e.g).
- Hands-on expertise with SQL and modern data tools (e.g., Snowflake, dbt, Spark)
- Experience designing and deploying scalable ETL/ELT pipelines and schema management solutions
- Deep knowledge of AWS cloud ecosystems, networking/security, common IaC tools (Terraform) and building systems for scale
- Ability to provide architectural guidance (e.g., API gateways, cloud-native systems), making trade-offs to unblock critical decisions that balance engineering scalability with business vision
- Proven track record delivering end-to-end analytics solutions to support Data Science, Experimentation, and Machine Learning applications
Responsibilities
- Balance strategic direction with hands-on contributions in development of scalable and resilient data engineering solutions using modern cloud platforms (e.g., AWS, GCP, Azure) and tools (e.g. Snowflake,Redshift, dbt, Airflow, Prefect)
- Standardize team operations (workflows, documentation, packages) and improve visibility with metrics and alerts
- Ensure data quality, security, and governance standards across pipelines and platforms to drive operational excellence and visibility
- Stay up to date with emerging technologies, trends, and best practices to drive adoption of new tools or approaches as needed
- Designing and deploying scalable ETL/ELT pipelines and schema management solutions
- Building systems for scale
- Provide architectural guidance (e.g., API gateways, cloud-native systems), making trade-offs to unblock critical decisions that balance engineering scalability with business vision
Other
- Lead, mentor, and grow a team of data engineers, fostering a collaborative and high-performing culture
- Translate high-level business goals into clear, prioritized execution plans—establishing a roadmap, allocating resources effectively, and adapting project plans as needed to ensure timely, high-quality delivery, even when inputs are unclear
- Collaborate regularly with cross-functional teams such as Product, Analytics, Security, IT, and external stakeholders to ensure delivery of high-quality data products
- 7+ years of experience in data engineering, including 2+ years in a team-lead or management role with a positive track record of recruiting, developing, and mentoring high-performing teams
- High degree of ownership and adaptability—proactive in identifying opportunities, driving improvements, and navigating ambiguity with strong project planning and organizational skills to anticipate risks, rework plans as needed, and successfully guide multiple initiatives simultaneously
- Excellent communicator and collaborator, skilled at translating business needs into scalable technical solutions from a variety of stakeholders, from engineers to executives
- We are a remote-first company and work happens across many time-zones – you may be required to occasionally perform duties outside your standard working hours
