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.
147k – 179k/yr
Remote7+ YOEData Engineering
About the role
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)
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