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.