Principal Data Engineer
Tasks
- Assess and mitigate risks
- Build dimensional models and data warehouse designs
- Coordinate across engineering and product teams
- Decompose strategic direction into projects
- Define strategic outcomes and influence roadmaps
- Design scalable cost effective data solutions
- Develop data pipelines using infrastructure as code and CI CD
- Drive data engineering best practices
- Escalate issues while solving in parallel
- Estimate work with unknowns and coach estimation best practices
- Implement data quality frameworks and validation testing
- Improve customer end to end experience
- Integrate BI platforms for business insights
- Lead data projects and set technical direction
- Manage stakeholders and negotiate in complex scenarios
- Mentor and develop engineers and leaders
- Migrate production systems to ELT platforms
- Orchestrate workflows with Airflow Dagster or Databricks Workflows
- Plan communicate and execute challenging problems
- Process data at scale with Apache Spark
- Propose organization processes to improve throughput and engagement
- Set codebase health standards
- Simplify complex high ambiguity problems
- Translate business needs into data projects
- Use Git branching strategies for collaborative development
Perks/Benefits
- 401k matching
- Access to Perks at Work program
- EAP
- EAP health advocacy program
- Education budget
- Flexible spending account
- Group life disability and AD and D insurance
- Health savings account
- Health, dental, and vision insurance
- Paid Holidays
- Paid time off
Skills/Tech-stack
AWS | Airflow | Apache Spark | Azure | CI/CD | Dagster | Data Quality | Data Validation | Data Vault | Data Warehouse | Databricks | Databricks Workflows | Dimensional Modeling | GCP | Git | Go | Infrastructure as Code | Kafka | Looker | Pulumi | Python | Snowflake | Tableau | Terraform | Version control | “as-code”
Education
N/A
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