AWS Cloud Engineering

LanceSoft•Sunnyvale, CA

3d•Onsite

About The Position

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.

Requirements

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.

Nice To Haves

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).

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.