Staff Software Engineer (Data Platform)

Job description

**Staff Software Engineer (Data Platform)** Join our dynamic team at the forefront of cutting-edge technology as we seek a seasoned Staff Data Engineer. Embark on a journey where your deep-rooted expertise in distributed systems, data architectures, and large-scale processing becomes the cornerstone of building high-performance data platforms. This pivotal role demands proficiency in designing and scaling compute and I/O-intensive data systems, ensuring reliability, efficiency, and cost optimization across the data lifecycle. **Responsibilities:** ● Design and build scalable data platform components for batch and real-time data processing. ● Architect, develop, and operationalize large-scale data systems across ingestion, transformation, and serving layers. ● Build and manage robust data pipelines ensuring high reliability, scalability, and cost efficiency. ● Develop reusable frameworks and tooling to accelerate productivity for data engineers and data scientists. ● Leverage expertise in Python, Airflow, SQL, and cloud platforms to build production-grade data solutions. ● Optimize query performance and data models using strong understanding of columnar OLAP systems such as ClickHouse, Doris, and StarRocks. ● Implement streaming and near real-time data processing systems. ● Translate complex business requirements into scalable and efficient data platform solutions. ● Work collaboratively with cross-functional teams and provide technical leadership and mentorship. ● Drive architectural decisions by evaluating tradeoffs and selecting the right tools for the problem. **Requirements:** ● Bachelor's Degree in Computer Science, Information Technology, or a similar discipline. ● 8+ years of professional experience in data engineering, backend systems, or distributed systems. ● Proven experience building scalable data platforms and large-scale data systems. ● Strong experience with ETL pipelines, data integration, and workflow orchestration systems such as Airflow or Temporal. ● Hands-on experience in Python and SQL with strong understanding of data warehouse concepts. ● Experience working with distributed OLTP/OLAP databases such as ClickHouse, PostgreSQL, Cassandra, or Elasticsearch. ● Knowledge of messaging and streaming systems such as Kafka. ● Experience with cloud platforms (AWS/GCP) and big data tools such as Spark. ● Strong understanding of columnar storage systems and query optimization techniques. ● Solid understanding of distributed systems fundamentals and associated tradeoffs. ● Experience working with containers and orchestration tools such as Docker and Kubernetes. ● Strong Linux fundamentals and system-level debugging skills. ● Familiarity with modern data architectures such as Lakehouse (Iceberg, Hudi, Delta) is a plus.