Lead Data Engineer
New
WorldwideFull-TimeLead
Salary185,000 - 225,000 USD per year
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Job Details
- Experience
- 7+ years
- Required Skills
- AWSGraphQLPythonSQLGCPKafkaSnowflakeAirflowAzureCI/CDBigQuerydbtRedshift
Requirements
- 7+ years of experience in data engineering
- 2+ years in a technical leadership role
- Strong proficiency in Python
- Strong proficiency in SQL
- Experience in designing, building, and maintaining cloud-based data pipelines
- Experience with orchestration tools such as Airflow, Dagster, Prefect, or Temporal
- Hands-on experience with cloud data platforms (AWS, GCP, or Azure)
- Experience with modern data stack tools
- Deep understanding of data warehousing concepts
- Experience with platforms like Snowflake, BigQuery, or Redshift
- Strong software engineering fundamentals including testing, CI/CD, version control
- Track record of optimizing data systems for performance, reliability, and cost efficiency at scale
- Excellent communication skills and ability to collaborate with cross-functional teams
Responsibilities
- Design and build scalable data pipelines to ingest, process, and transform blockchain data, trading events, user activity, and market signals at high volume and low latency
- Architect and maintain data infrastructure that powers real-time trading analytics, P&L calculations, leaderboards, market cap tracking, and liquidity monitoring across the platform
- Own ETL/ELT processes that transform raw onchain data from multiple blockchains into clean, reliable, and performant datasets used by product, engineering, analytics, and ML teams
- Build and optimize data models and schemas that support both operational systems (serving live trading data) and analytical use cases (understanding market dynamics and user behavior)
- Establish data quality frameworks including monitoring, alerting, testing, and validation to ensure pipeline reliability and data accuracy at scale
- Collaborate with backend engineers to design event schemas, data contracts, and APIs that enable real-time data flow between systems
- Partner with product and analytics teams to understand data needs and translate them into robust engineering solutions
- Provide technical leadership by mentoring engineers, conducting code reviews, establishing best practices, and driving architectural decisions for the data platform
- Optimize performance and costs of data infrastructure as we scale to handle exponentially growing trading volumes
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