You Will:
- Lead and mentor a team of Data Platform Engineers to develop Gopuff’s central data platform, fostering a collaborative and innovative team culture
- Drive continuous improvement within the team by developing practices around professional development, performance management, and hiring
- Provide clear technical direction and support for the team, ensuring the successful execution of data platform projects and initiatives
- Collaborate with engineering and product leadership to translate business requirements into effective technical solutions
- Develop and promote best practices for data collection, storage, and processing that impact the company-wide data strategy across Gopuff’s data lake and warehouse
- Architect and implement large-scale data platforms that enable analytics, data science, and machine learning in a multi-cloud environment
- Partner with software and analytics engineering teams to establish data contracts and improve data quality at every stage of the data lifecycle
- Manage project timelines, resource allocation, and team performance, ensuring that deliverables are met on schedule and within scope
You Have:
- 5+ years of experience in a data engineering or cloud/infrastructure engineering role
- 3+ years of engineering management experience
- Experience collaborating with functional stakeholders and establishing a roadmap that aligns with business priorities
- Experience with organizational design, team development, hiring, and performance management
- Experience building batch data pipelines using DAG-based tools such as Dagster or Airflow
- Experience deploying applications and service to Kubernetes and using related tools in the Kubernetes ecosystem (i.e. Helm, ArgoCD, Istio)
- Experience implementing DevOps best practices within the data platform, including solutions for CI/CD, data observability, monitoring, and lineage
- Experience in producing and consuming topics to/from Apache Kafka, AWS Kinesis, or Azure Event Hubs
- Experience with Infrastructure as code tools such as Terraform
- Experience developing real-time data pipelines using frameworks such as Apache Beam, Flink, Storm, Spark Streaming, etc.
- Experience with data warehouses, data lakes, and their underlying infrastructure
- Proficiency in Python, SQL, RESTful API development
- Experience with cloud computing platforms such as Azure, AWS
- Experience with data governance, schema design, and schema evolution
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