Data Engineer

Why join

• ▹Build real-time data projects from zero to one, from pipeline design to production operations
• ▹Work across the whole data stack, including real-time computing, real-time warehousing, OLAP and governance, not just SQL and reports
• ▹Senior data engineers on the team for technical discussion and project guidance
• ▹Unlimited Claude Code and Codex usage, plus bonuses and equity for core contributors

What you will do

• ▹Develop real-time Java/Flink jobs for cleansing, transformation, aggregation, alerting and metrics, and own their release, operation and troubleshooting
• ▹Build high-concurrency data collection services in Go against RPC and third-party APIs, handling reconnects, rate limits, duplicate or missing messages and backfills
• ▹Ingest, clean, transform and model multi-source data, and build and maintain ETL pipelines and ODS, DWD and DWS warehouse layers
• ▹Onboard, model, query-tune and performance-tune OLAP databases such as Doris, StarRocks and ClickHouse
• ▹Own data quality and job monitoring, resolve latency, duplication, gaps and cross-source inconsistencies, and build validation and reconciliation rules into pipelines
• ▹Contribute to metadata, lineage and dataset standards, unify data definitions, and build high-quality, traceable data assets
• ▹Set up alerting, backfill and self-healing for data delays, deviations and job failures, and refine rerun, replay and repair procedures
• ▹Work with product, operations and analytics teams to turn business problems into practical data solutions

What we look for

• ▹Proficiency in Java or Go, able to iterate independently and troubleshoot production issues
• ▹Solid SQL for common querying, aggregation, joins and tuning
• ▹Familiarity with one or more of Flink, Spark, Kafka or Doris; experience writing native Flink jobs is a plus
• ▹Familiarity with MySQL/PostgreSQL, Redis and message queues such as Kafka or RabbitMQ
• ▹Familiarity with OLAP databases such as StarRocks, Doris or ClickHouse
• ▹Understanding of warehouse layering and ETL, with a strong feel for data and the ability to spot anomalies and trace root causes
• ▹Able to diagnose issues from logs, monitoring and data results
• ▹Good communication and a strong drive to learn, with interest in going deep on real-time computing and big data

Nice to have

• ▹Flink project experience, including Flink SQL, DataStream, CEP, state management and checkpointing
• ▹Experience with real-time warehousing, real-time metrics, real-time risk control, data sync or CDC
• ▹Experience deploying, monitoring, alerting on and tuning jobs in production
• ▹Experience combining Java backend systems with big data jobs
• ▹Zero-to-one data engineering experience, or you have built data monitoring and quality validation systems
• ▹Experience processing raw on-chain data, including block sync, event log parsing, chain reorgs and reconciliation
• ▹Experience with metadata and lineage tools, or rolling out enterprise data governance standards

Growth path

Real-time data engineer

Tech stack

• Java
• Go
• Flink
• Kafka
• SQL
• Doris
• StarRocks
• ClickHouse
• Spark
• PostgreSQL