Tech Lead - Data Engineering


Job Description

  • Work with the team to design and implement features for the data platform.
  • Automate and optimize data pipelines and set up monitoring and feedback systems
  • Write and optimize ETL from/to the product and homegrown or 3rd party tools.
  • Drive vendor POCs for data and analytics solutions.
  • Translate data consumption requirements into technical specifications, including data streams, integrations, transformations, databases, and data warehouses
  • Collaborate cross functionally to revamp data models that power business critical internal and customer-visible metrics.
  • Advocate for data driven thinking and help elevate data literacy across the company
  • Mentor and learn from peers to build a cohesive culture and best practices on data at Eventbrite
  • Outstanding interpersonal and communication skills
  • Strong analytical, problem solving and critical thinking skills
  • Proficiency in Python and SQL
  • Experience running ETL processes on large scale data sets
  • Familiarity with Data Engineering tools such as Spark, Hive, Hadoop, MySQL, Airflow, DynamoDB, EMR, Terraform, Kafka/Kinesis, Presto/Trino, Kubernetes etc.
  • Experience translating high level business questions to analytics needs and implementation
  • Data modeling experience and ability to partner with technical and non technical stakeholders
  • 9 years of experience in Software or Data Engineering, building high quality production software
  • Familiar with Data Science, Machine Learning, Data Analytics, and the relevant technologies that support them.
  • Experience with AWS products and services
  • Experience architecting and/or running data infrastructure
  • Active Eventbrite user with a passion for live events
  • Skilled in various forms of data modeling on structured, semi-structured and unstructured data
  • Familiarity with server-side frameworks, such as Django, Express, Rails, or Net.
  • Familiarity with database optimization and scaling approaches including indexing, partitioning, shading, clustering, in memory tables, horizontal and vertical scaling.
  • Familiarity with managing large datasets and understanding the complexities of merging large databases, meeting security audit requirements, and implementing data retention policies.

Key Skills

Security audit; Product engineering; Data modeling; Django; Analytical; MySQL; Machine learning; Monitoring; SQL; Python

About Company

A global platform that allows anyone to create, share, find and attend events that fuel their passions

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