Staff Data Engineer

What you'll do

• Architect, build, and deploy high-performance data solutions across streaming, modeling, analytics databases, and real-time processing.
• Operate reliable batch and real-time pipelines, addressing data quality, consistency, performance, and scale.
• Own initiatives from design through production and maintenance, and mentor engineers through technical leadership and code reviews.

What they ask for

• Deep expertise in data engineering, distributed systems, and modern cloud infrastructure.
• Fluency in SQL and Python, with hands-on experience in large-scale data ecosystems such as Spark, Kafka, Airflow, dbt, ClickHouse, BigQuery, or Snowflake.
• Experience designing and operating high-volume batch and real-time pipelines with attention to quality, observability, and performance.
• Experience modeling complex datasets and driving technical initiatives, making architectural decisions, and mentoring engineers.

Nice to have

• Experience with cryptocurrency and blockchain data; event tracking; or consumer tech or fintech products.
• Data visualization (especially Omni/Looker), statistical methods and causal inference, Dagster or DBT, or machine learning.

Tools

SQL, Python, Spark, Kafka, Airflow, dbt, ClickHouse, BigQuery

AI focus

The role may enable machine learning teams through data platforms; machine learning experience is preferred.