Senior Engineer - Hyperscale Analytics
Core
Design and scale next-generation data processing and analytics platforms powering OLTP, OLAP, and large-scale distributed data systems.
Role type
Senior IC distributed systems engineer (hyperscale analytics)
Builds
High-throughput pipelines and services handling billions of records daily for real-time transactions and AI-driven decisioning
Domain
Cloud-scale data infrastructure and distributed processing
Deliverable
production ML models | product features
Required skills
Distributed data processing frameworks (Spark, Flink), Cloud-scale data architecture (AWS/Azure/GCP), Python/Java/Scala/Go, Modern data warehouse/lakehouse technologies (Snowflake, Databricks, BigQuery, Redshift), Data modeling and pipeline orchestration (Airflow, dbt)
Preferred skills
HTAP systems, Data lakehouse formats (Parquet, ORC, Delta, Iceberg, Hudi), Containerized deployments (Docker, Kubernetes), Query engine development
Technologies
Apache Spark, Flink, Presto/Trino, Kafka Streams, Snowflake, BigQuery, Redshift, Cassandra, HDFS, Delta Lake, Iceberg, Airflow, dbt, Docker, Kubernetes
Responsibilities
Design and implement scalable OLTP systems for real-time workloads; Build and optimize large-scale batch and streaming pipelines; Optimize systems for low-latency queries and high-throughput ingestion; Develop and integrate with modern storage and processing systems; Ensure high availability and monitoring across large compute and storage clusters; Partner with data scientists and product teams to build unified data platforms
Seniority
Senior, hands-on IC