Staff Data Engineer
Skills
Amazon RedshiftData RetentionData WarehousingDownstream Oil And GasModelingRecruitingSales
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- Experience building a data engineering function from scratch at a growing startup
- Strong expertise in data modeling and SQL
- Extensive experience building data pipelines in Python or Go
- Experience with a cloud data warehouse such as Snowflake BigQuery or Redshift
- Experience with pipeline orchestration or transformation tooling
- Experience handling sensitive data with access control and retention practices
- Willingness to work collaboratively on a SQL or Go coding challenge
- Intellectual curiosity and willingness to learn new technologies
- Comfort working directly with stakeholders across the company
- No-ego mindset focused on collaboration transparency and feedback
Nice to have
- Go preferred
- Mathematics or statistics background
- Airflow familiarity
- dbt familiarity
Day to day
- Design and build data pipelines that ingest data from multiple internal sources into a central warehouse
- Create data models and schemas that are performant well-documented and adaptable as business needs evolve
- Implement data quality checks and validation at every stage so bad data is caught early and does not reach downstream tables
- Partner with product engineering finance and revenue stakeholders to understand data needs and deliver reliable self-serve analytics
- Handle sensitive data responsibly with access control redaction and retention policies for customer and user information
Hiring process
- Zoom meeting with a Teleport recruiter
- Zoom meeting with the Hiring Manager
- Coding challenge collaboration via Slack and GitHub
- Final Zoom review with the Hiring Manager and interview team
- Offer decision