Senior Data Engineer
Senior Data Engineer leads data stack evolution, building scalable pipelines and infrastructure for analytics, reporting, and self-serve tools using Snowflake, dbt, AWS. Requires 7+ years experience, BS/MS, expertise in SQL, Python, orchestration tools.
About the job
Responsibilities
- Partner with Product, Analytics and Engineering to build scalable systems unlocking data value from backend databases, event streams, and marketing platforms
- Lead technical vision and architecture with short- and long-term horizons
- Work with analytics to create company-wide alignment through standardized metrics
- Support internal use cases like financial reporting, product analytics, and operational metrics
- Enable external use cases like customer-facing dashboards, self-serve analytics, and next best action in product
- Manage complete data stack from ingestion through consumption
- Build tools to increase transparency in company-wide business outcomes
- Work with DevOps to deploy and maintain data solutions in AWS
- Define data quality and security framework; promote data engineering best practices
Desired Skills & Experience
Education & Experience
- BS/MS in Engineering, Computer Science, Mathematics, or related field
- 7+ years in Data or Analytics Engineering
- Strong problem-solving and communication skills; comfortable in fast-paced, cross-functional environments
Data Engineering & Pipelines
- Enterprise architecture and data modeling (relational, dimensional, semantic)
- Expert in SQL and data modeling
- Proven experience in data warehouse design with Snowflake
- Hands-on with DBT for transformations
- Experience with orchestration/ingestion: Airflow, Prefect, Airbyte, Fivetran, Kafka
- Familiar with ELT, schema-on-read, DAGs, performance optimization
Cloud & Infrastructure
- Experience with AWS (S3, RDS, Redshift)
- Familiar with Terraform, Docker, containerized workflows (bonus)
- Skilled in structured/semi-structured/columnar formats (JSON, Parquet, ORC)
Analytics & Enablement
- Building/supporting semantic layers for self-serve analytics
- Proficient with BI tools: Looker, Tableau, Sisense
- Standardizing metrics for trusted data access
Programming & Scripting
- Proficient in Python and Unix/Linux scripting
- Comfortable with APIs (e.g., curl)
Bonus Points
- AWS DevOps: Terraform, Kubernetes, Docker
- Project & Change Management in Agile (SCRUM, Kanban)
- Real-time ETL: Kafka streaming, AWS Kinesis
Base Compensation Range
$146,500 - $179,000 (base salary; additional bonus/commission possible)
Skills
SQL, Snowflake, dbt, Airflow, AWS, Python, Kafka, Fivetran, Airbyte, Looker, Terraform, Docker, Redshift, S3, Prefect
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