Senior Engineer - Hyperscale Analytics

Veeam is the Data and AI Trust Company, specializing in helping organizations ensure their data and AI are fully understood, secured, and resilient to enable the acceleration of safe AI at scale. As the market leader in both data resilience and data security posture management, Veeam is built for the convergence of identity, data, security, and AI risk. Headquartered in Seattle with offices in more than 30 countries, Veeam protects over 550,000 customers worldwide, who trust Veeam to keep their businesses running. Join us as we go fearlessly forward together, growing, learning, and making a real impact for some of the world’s biggest brands.

About the Role

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.

What You’ll Do

Transactional & Analytical Systems: Design and implement highly scalable OLTP systems for real-time workloads and OLAP systems for complex analytical queries on massive datasets

Distributed Processing: Build, optimize, and maintain large-scale batch and streaming pipelines using frameworks such as Apache Spark, Flink, Presto/Trino, or Kafka Streams

System Performance & Scale: Optimize systems for low-latency queries, high-throughput ingestion, and interactive analytics, ensuring seamless performance as data volumes scale to petabytes

Data Infrastructure: 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

Reliability & Observability: Ensure high availability, reliability, and monitoring across large compute and storage clusters with automated failover and recovery

Collaboration: Partner with data scientists, ML engineers, and product teams to build unified, secure, and cost-efficient data platforms

What You’ll Bring

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

Bonus Skills

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

What you'll get

Unlimited paid time off, 12 paid holidays including 4 global VeeaMe Days for self-care and 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, plus paid volunteer time

AirVet: 24/7 virtual veterinary care at no cost

Legal services, ide