Staff Data Engineer

What you'll do

• Lead the batch analytics team by providing the groundwork to modernize our data analytics architecture
• Design and maintain our data warehouse to facilitate analysis across hundreds of systems events
• Rethink and influence strategy and roadmap for building efficient data solutions and scalable data warehouses
• Review code for style and correctness across the entire team
• Write production-grade Redshift, Athena, Snowflake & Spark SQL queries
• Manage and maintain Airflow ETL jobs
• Test query logic against sample scenarios
• Work across teams to gather requirements and understand reporting needs
• Investigate metric discrepancies and data anomalies
• Debug and optimize queries for other business units
• Review schema changes across various engineering teams
• Maintain high-quality documentation for our metrics and data feeds 
• Work with stakeholders in Data Infrastructure, Engineering, Product and Customer Strategy to assist with data-related technical issues and build scalable cross platform reporting framework
• Participate in, and co-manage our on-call rotation to keep production pipelines up and running

What you'll need

• 7+ years industry experience with clear examples of strategic technical problem solving and implementation
• Expertise in at least one flavor of SQL. (We use Amazon Redshift, MySQL, Athena and Snowflake)
• Strong experience with data warehousing (e.g. Snowflake (preferred), Redshift, BigQuery, or similar)
• Experience with dimensional data modeling and schema design
• Experience using developer-oriented data pipeline and workflow orchestration (e.g. Airflow (preferred), dbt, dagster or similar)
• Experience with cloud computing services (AWS (preferred), GCP, Azure or similar)
• Proficiency in a high-level programming language, especially in terms of reading and comprehending other developers’ code and intentions. (We use Python, Scala, and Go)
• Deep technical knowledge of data exchange and serialization formats such as Protobuf, YAML, JSON, and XML
• Familiarity with BI & Analytics tools (e.g. Looker, Tableau, Sisense, Sigma computing or similar)
• Familiarity with streaming data technologies for low-latency data processing (e.g. Apache Spark/Flink, Apache Kafka, Snowpipe or similar)
• Familiarity with Terraform, Kubernetes and Docker
• Understanding of modern data storage formats and tools (e.g. parquet, Avro, Delta Lake)
• Knowledge of modern data design and storage patterns (e.g. incremental updates, partitioning and segmentation, rebuilds and backfills)

What we'd like to see

• Experience working at a startup preferred
• Excellent communication skills - (Slack/Email/Documents)
• Experienced with end user management & communication (cross team as well as external)
• Must thrive in a fast paced environment and be able to work independently with urgency
• Can work effectively remotely (able to be proactive about managing blockers, proactive on reaching out and asking questions, and participating in team activities)
• Experienced in writing technical data design docs (pipeline design, dataflow, schema design)
• Can scope and breakdown projects, communicate and collaborate progress and blockers effectively with your manager, team, and stakeholders
• Good at task management & capacity tracking (JIRA (preferred))