Senior Data Engineer (Remote)
Zencastr · Remote · San Francisco Office ·
COMPENSATION
€•• – ••k
Listed on the employer's job board (Ashby)
- Fully remote
- Senior level
- SQL + dbt
- Data modeling
- First data hire
As the first dedicated Data Engineer, you will design and own the data foundation powering analytics and decision-making. You will partner with an experienced data team to transform institutional knowledge into a single, well-modeled warehouse using Kimball-style principles.
The work involves end-to-end ownership of ingestion, transformation, and modeling, with a specific focus on identity resolution across disparate systems. You will establish best practices for governance, testing, and performance while collaborating cross-functionally to support business needs.
What you'll do
- Design and build a conformed, Kimball-style dimensional model for operational and transactional data
- Own end-to-end ingestion, including capturing historical changes from sources without native history
- Consolidate transformation logic into a single governed layer with version control and testing
- Implement identity resolution to connect entities across systems with different identifiers
- Establish best practices for data modeling, documentation, testing, and governance
- Monitor and optimize performance, reliability, and cost efficiency of pipelines and queries
- Encode business metric definitions to prevent reporting drift across teams
- Improve data freshness by moving core operational data toward near-real-time availability
What you'll need
- 5+ years of experience in data engineering or analytics engineering
- Proven track record of building and owning a dimensional model in production
- Strong proficiency in SQL and experience with document-based operational databases
- Experience with analytical data warehouses such as BigQuery, Snowflake, or Redshift
- Hands-on experience with transformation frameworks like dbt or Dataform
- Proficiency with orchestration tools such as Airflow, Dagster, or Prefect
- Experience with data ingestion or event streaming platforms like Segment or Pub/Sub
- Ability to explain technical tradeoffs clearly to non-engineering stakeholders
Nice to have
- Experience with change data capture patterns from operational databases
- Familiarity with subscription billing data including proration and refunds
- Experience with distributed processing frameworks like Spark or Dataflow
- Previous experience as a first or early data hire in a growing organization
Stack
- SQL
- MongoDB
- BigQuery
- Snowflake
- Redshift
- dbt
- Dataform
- Airflow
- Dagster
- Prefect
- RudderStack
- Segment
- Pub/Sub
- Spark
- Beam
- Dataflow
How you'll work
- Fully remote position
- Collaborate with existing data, engineering, and technical teams