Staff Software Engineer (Data Platform)

About this role

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.