Senior Engineer - Hyperscale Analytics

Veeam Software•San Jose, CA

3d•$237,800 - $441,500

About The Position

We are seeking exceptional Senior Engineer- Hyperscale Analytics to design and scale next-generation data processing and analytics platforms that power OLTP, OLAP, and large-scale distributed data systems. You will build and optimize pipelines and services that handle billions of records daily, enabling real-time transactions, analytical insights, and AI-driven decisioning.

Requirements

6+ years of professional software engineering experience, with a significant portion focused on data infrastructure, distributed systems, or large-scale analytics platforms
Deep experience with distributed data processing frameworks (e.g., Spark, Flink, or similar)
Strong background in cloud-scale data architecture (AWS, Azure, or GCP) — data lakes, warehouses, streaming platforms
Proficiency in one or more of: Python, Java, Scala, or Go
Experience with modern data warehouse/lakehouse technologies (e.g., Snowflake, Databricks, BigQuery, Redshift)
Solid understanding of data modeling, ETL/ELT design, and pipeline orchestration (e.g., Airflow, dbt)
Track record of designing for scale, reliability, and cost efficiency in production systems

Nice To Haves

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

Responsibilities

Design and implement highly scalable OLTP systems for real-time workloads and OLAP systems for complex analytical queries on massive datasets
Build, optimize, and maintain large-scale batch and streaming pipelines using frameworks such as Apache Spark, Flink, Presto/Trino, or Kafka Streams
Optimize systems for low-latency queries, high-throughput ingestion, and interactive analytics, ensuring seamless performance as data volumes scale to petabytes
Develop and integrate with modern storage and processing systems (e.g., Snowflake, BigQuery, Redshift, Cassandra, HDFS, Delta Lake, Iceberg) to support hybrid analytical/transactional workloads
Ensure high availability, reliability, and monitoring across large compute and storage clusters with automated failover and recovery
Partner with data scientists, ML engineers, and product teams to build unified, secure, and cost-efficient data platforms

Benefits

Unlimited paid time off
12 paid holidays including 4 global VeeaMe Days for self-care
24 paid volunteer hours annually through Veeam Cares
Paid parental leave: 8 weeks for all parents, 16 weeks for birthing parents
Medical, dental, and vision coverage starting on your first day
Mental health support, therapy sessions, and digital wellness tools via our Employee Assistance Program
401(k) retirement plan with company matching contributions
Fertility, adoption, and surrogacy support through Maven
AirVet: 24/7 virtual veterinary care at no cost
Legal services, identity protection, and supplemental health insurance options
Tax-advantaged spending accounts for healthcare, dependent care, and commuting
Opportunities to learn and grow through on-demand libraries (LinkedIn Learning, O’Reilly), mentoring, workshops, and learning events like our annual Global Day of Learning