Staff Data Engineer

You'll help build, maintain, and scale the data pipelines that bring together data from various internal and external systems into the data warehouse. You'll partner with stakeholders across Data, Engineering, Operations, Data Science, Go-to-Market, and Finance teams to understand their analysis needs and consumption patterns, and work with upstream engineering teams to improve data logging practices. As the internal expert on data engineering, you'll participate in architectural decisions, evangelize best practices for data processing, modeling, and warehouse development, and advise engineers and cross-functional partners on how to most efficiently use the data tools. You'll have the opportunity to influence not only the data systems but also the company's broader drone and global operations.

Responsibilities

• Help build, maintain, and scale data pipelines that bring together data from various internal and external systems into the data warehouse
• Partner with internal stakeholders to understand analysis needs and consumption patterns
• Partner with upstream engineering teams to enhance data logging patterns and best practices
• Participate in architectural decisions and help plan for the company's data needs as it scales
• Adopt and evangelize data engineering best practices for data processing, modeling, and lake/warehouse development
• Advise engineers and other cross-functional partners on how to most efficiently use data tools

Requirements

• Have 7+ years experience building large scale data platforms
• Experience in Data Engineering, and/or Analytics Engineering, building scalable data warehouses
• Proficient with Dimensional Modeling (Star Schema, Kimball, Inmon) and Data architecture concepts, able to coach and influence others to up-level the craft of Data Engineering
• Fantastic collaboration and communication skills, demonstrated by successful large-scale projects spanning multiple teams
• Advanced SQL skills (ease with window functions, defining UDFs)
• Experienced with Python, Spark for building and maintaining data pipelines & ETL/ELT processes
• Experienced working with dbt and Snowflake, BigQuery, Redshift or other data warehouses
• Experience implementing real-time and batch data pipelines with tight SLOs and complex transformation requirements
• Develop data models, schemas and standards for event data
• Optimize data storage and access patterns for fast querying
• Improve data reliability, discoverability and observability
• Familiarity with Data Engineering tooling: ingesting, testing transformations, lineage, orchestration, publishing data, metric layers
• Familiarity with storage layers like Hudi, Delta Lake and Iceberg
• Aptitude for product analysis, dashboarding, and reporting
• Familiarity with infrastructure tooling such as Terraform/Pulumi and worked with Kubernetes
• Proficiency with AWS cloud
• Experience building streaming applications or pipelines using async messaging services or distributed streaming platforms like Apache Kafka
• Knowledge of Airflow or some other orchestration tool
• Experience with Spark or PySpark
• Experience with event-driven architecture and streaming data processing frameworks like Kafka, Spark, Flink
• Experienced with time-series databases like Clickhouse, InfluxDB

Benefits

• Stock option incentive program
• Company paid healthcare
• Flexible work arrangements
• Company sponsored team-lunches
• Company retreats