Data Engineer � Snowflake & Apache Doris

About the Role

We are seeking an experienced Data Engineer to design, build, and optimize scalable data pipelines and analytics infrastructure. The ideal candidate has hands-on expertise with Snowflake for cloud data warehousing and Apache Doris for real-time OLAP analytics, and is comfortable working across the full data lifecycle — from ingestion to transformation to serving high-performance queries for analytics and BI teams.

Location: Sunnyvale, CA – Onsite.

Responsibilities

• Design, build, and maintain robust, scalable ETL/ELT pipelines to ingest structured and semi-structured data from multiple sources into Snowflake and Apache Doris.
• Architect and optimize data models, schemas, and partitioning strategies in Snowflake and Doris to support high-throughput, low-latency analytical workloads.
• Tune query performance, indexing, materialized views, and storage layout in Doris for real-time OLAP use cases.
• Manage Snowflake warehouse sizing, cost optimization, resource monitors, and query performance tuning.
• Build and maintain data orchestration workflows (e.g., Airflow, dbt, or similar) to automate pipeline scheduling, dependency management, and monitoring.
• Implement data quality checks, validation frameworks, and observability/alerting for pipeline reliability.
• Collaborate with data analysts, data scientists, and BI teams to understand reporting requirements and translate them into performant data models.
• Support migration and integration projects between transactional systems, data lakes, Snowflake, and Doris.
• Ensure data governance, security, and access control best practices (RBAC, data masking, encryption) across platforms.
• Document data architecture, pipeline logic, and operational runbooks.

Required Qualifications

• 7+ years of experience as a Data Engineer or in a similar role.
• Hands-on production experience with Snowflake — including SQL scripting, warehouse management, Snowpipe, Streams/Tasks, and performance tuning.
• Hands-on experience with Apache Doris — including cluster architecture (FE/BE nodes), table models (Aggregate, Unique, Duplicate), materialized views, and real-time data loading (Stream Load, Routine Load, Broker Load).
• Strong SQL skills and experience with data modeling (star/snowflake schemas, dimensional modeling).
• Proficiency in Python commonly used in data engineering.
• Experience with workflow orchestration tools (Apache Airflow, dbt, Dagster, or similar).
• Familiarity with streaming/messaging systems (Kafka, Pulsar, or similar) for real-time data ingestion.
• Solid understanding of data warehousing concepts, OLAP vs. OLTP design, and distributed systems fundamentals.
• Experience with version control (Git) and CI/CD practices for data pipelines.

Preferred Qualifications

• Experience migrating workloads from traditional data warehouses to Snowflake and/or Doris.
• Familiarity with cloud platforms (AWS, GCP, or Azure) and infrastructure-as-code tools (Terraform, CloudFormation).
• Experience with containerization/orchestration (Docker, Kubernetes) for deploying Doris clusters.
• Knowledge of BI/visualization tools (Tableau, Looker, Superset, Power BI).
• Background in cost optimization and capacity planning for large-scale analytical systems.
• Contributions to open-source data engineering projects (e.g., Apache Doris community).