Staff Data Platform Engineer
Description
Position Summary:
We are looking for a talented Staff Data Engineer to join our Data Engineering team, to participate in the development of data pipelines for blockchain data processing. This is a remote role, and we are flexible with considering applications from anywhere in Europe.
More details: crystalblockchain.com
Duties and responsibilities:
Design and evolve data pipeline architecture and storage systems, driving technical direction across the team;
Build and deliver high-quality data pipelines end-to-end, from initial design through production deployment;
Mentor engineers, raise the technical bar through code reviews, and unblock teammates on complex problems;
Own team outcomes — set expectations, ensure delivery quality, and take accountability for results.
Required:
8+ years of hands-on software engineering experience, with significant depth in data pipelines, backend services, or data platform engineering;
Deep experience designing and operating data lakes/warehouses/lakehouses at production scale;
Experience in scaling data pipelines and good understanding of trade-offs (performance, resources)
Expert Python skills: you write clean, performant, testable code and can establish standards for others;
Experience across the modern data processing stack e.g., Kafka or Redpanda (real-time ingestion, delivery semantics), Flink or Spark (stream and batch processing, stateful operations), Airflow or Dagster (scheduling, backfills, dependency management);
Expert-level SQL: complex joins, query planning and optimization, schema design across both OLTP and OLAP systems;
Strong database architecture skills;
Solid distributed systems experience;
Comfortable leading technical discussions, building consensus on architectural decisions, and being the person the team turns to when things get hard;
Team-oriented work and good communication skills are an asset;
Proficiency in English.
Would be a plus:
Experience working with distributed Clickhouse cluster;
Blockchain domain knowledge or an ability of mastering complex technical domains quickly;
Track record of driving engineering standards and best practices across a team.
No previous knowledge of Blockchain technology required.
Tech stack:
Languages & Frameworks: Python, FastAPI
Databases: PostgreSQL, ClickHouse, Redis, Snowflake
Infrastructure: Docker, Kubernetes, Terraform, AWS
Data Processing: Kafka, Apache Iceberg, Spark
Things we'll likely use in the future: Airflow / Dagster / Redpanda
You’ll get:
AI tool of your choice: Cursor or Claude Code.
We are looking for a talented Staff Data Engineer to join our Data Engineering team, to participate in the development of data pipelines for blockchain data processing. This is a remote role, and we are flexible with considering applications from anywhere in Europe.
More details: crystalblockchain.com
Duties and responsibilities:
Design and evolve data pipeline architecture and storage systems, driving technical direction across the team;
Build and deliver high-quality data pipelines end-to-end, from initial design through production deployment;
Mentor engineers, raise the technical bar through code reviews, and unblock teammates on complex problems;
Own team outcomes — set expectations, ensure delivery quality, and take accountability for results.
Required:
8+ years of hands-on software engineering experience, with significant depth in data pipelines, backend services, or data platform engineering;
Deep experience designing and operating data lakes/warehouses/lakehouses at production scale;
Experience in scaling data pipelines and good understanding of trade-offs (performance, resources)
Expert Python skills: you write clean, performant, testable code and can establish standards for others;
Experience across the modern data processing stack e.g., Kafka or Redpanda (real-time ingestion, delivery semantics), Flink or Spark (stream and batch processing, stateful operations), Airflow or Dagster (scheduling, backfills, dependency management);
Expert-level SQL: complex joins, query planning and optimization, schema design across both OLTP and OLAP systems;
Strong database architecture skills;
Solid distributed systems experience;
Comfortable leading technical discussions, building consensus on architectural decisions, and being the person the team turns to when things get hard;
Team-oriented work and good communication skills are an asset;
Proficiency in English.
Would be a plus:
Experience working with distributed Clickhouse cluster;
Blockchain domain knowledge or an ability of mastering complex technical domains quickly;
Track record of driving engineering standards and best practices across a team.
No previous knowledge of Blockchain technology required.
Tech stack:
Languages & Frameworks: Python, FastAPI
Databases: PostgreSQL, ClickHouse, Redis, Snowflake
Infrastructure: Docker, Kubernetes, Terraform, AWS
Data Processing: Kafka, Apache Iceberg, Spark
Things we'll likely use in the future: Airflow / Dagster / Redpanda
You’ll get:
AI tool of your choice: Cursor or Claude Code.