Data Engineer

Overview

We're looking for a Data Analytics Engineer to join our data team and help build and scale our analytics infrastructure from ingestion to dashboard. The role involves building and maintaining analytics pipelines in BigQuery, managing data ingestion and ETL processes, defining and maintaining business logic for metrics, and creating and updating internal dashboards.

Key Responsibilities

• Build and maintain analytics pipelines in BigQuery using dbt Cloud, including staging, transformation, and mart layers
• Manage and configure Airbyte ingestion streams and Hightouch reverse ETL syncs
• Partner with product engineering to ensure new features follow our event-driven instrumentation methodology and emit the right data from day one
• Define and maintain business logic for metrics construction, serving as the source of truth for how key metrics are calculated
• Build, update, and maintain internal dashboards in Looker Studio
• Build and maintain BigQuery datasets, views, and scheduled queries
• Maintain query performance and warehouse costs, proactively identifying opportunities to reduce spend
• Design and implement data backup and redundancy strategies
• Occasionally update the customer-facing dashboard layer in the product (TypeScript)
• Perform ad-hoc data analysis and produce one-off data pulls for customers as needed
• Identify recurring data requests and build automated, self-serve solutions to replace manual fulfillment
• Investigate BigQuery continuous queries for publishing metrics to Cloud Pub/Sub, enabling product engineering services to consume analytics data in near real-time
• Evaluate Cloud Dataflow for real-time and low-latency data processing use cases as the platform's needs evolve

Basic Qualifications

• 5+ years of experience in data engineering, BI analytics, or software engineering
• Expert-level SQL skills, particularly in BigQuery or comparable cloud data warehouses
• Hands-on experience with dbt (dbt Cloud preferred) for managing transformation pipelines
• Experience with data ingestion tools such as Airbyte, Fivetran, or similar
• Experience with reverse ETL tools such as Hightouch or Census
• Working knowledge of Python for data scripting, automation, and ad hoc analysis
• Strong understanding of event-driven data instrumentation and how analytics contracts should be defined alongside product features
• Track record of optimizing data warehouse costs and query performance
• Comfort working directly with engineering teams to define data requirements and instrumentation standards

Nice to Haves

• Experience with GCP data services beyond BigQuery (Cloud Dataflow, Pub/Sub, Cloud Functions)
• Familiarity with TypeScript or Kotlin
• Prior work with streaming or real-time data architectures
• Experience implementing data quality testing frameworks (e.g., dbt tests, Great Expectations, or similar)
• Familiarity with data governance practices, including documentation, lineage tracking, and access controls
• Experience working at a fast-growing startup where you owned the data stack end to end