Senior Engineer (Hyperscale Analytics)

- Solid understanding of data modeling, ETL/ELT design, and pipeline orchestration (e.g., Airflow, dbt) - 6+ years of professional software engineering experience, with a significant portion focused on data infrastructure, distributed systems, or large-scale analytics platforms - Strong background in cloud-scale data architecture (AWS, Azure, or GCP) — data lakes, warehouses, streaming platforms - Experience with modern data warehouse/lakehouse technologies (e.g., Snowflake, Databricks, BigQuery, Redshift) - Deep experience with distributed data processing frameworks (e.g., Spark, Flink, or similar) - Track record of designing for scale, reliability, and cost efficiency in production systems - Proficiency in one or more of: Python, Java, Scala, or Go - Experience with HTAP (Hybrid Transactional/Analytical Processing) systems or real-time analytics platforms - Familiarity with data lakehouse architectures and formats like Parquet, ORC, Delta, Iceberg, Hudi - Knowledge of containerized deployments (Docker, Kubernetes) and cloud-native data architectures (AWS Redshift, GCP BigQuery, Azure Synapse) - Background in query engine development or contributing to open-source OLAP/OLTP frameworks Join our team as a Senior Engineer specializing in Hyperscale Analytics. In this role, you will design and scale next-generation data processing and analytics platforms, build and optimize pipelines and services, and ensure high availability and reliability across large compute and storage…