Data Engineer
Description For Data Engineer
Auros, a premier algorithmic trading and market-making firm, is seeking a Senior Data Engineer to join their team. As a key player in the digital asset liquidity provision space, Auros facilitates 3-4% of global daily volumes across more than 50 venues worldwide.
The role presents a unique opportunity for an experienced Data Engineer to become both steward and champion for the firm's market and trading data archives and internal data products. You'll be working with existing data pipelines and databases while designing and implementing the next generation of Auros data and analytic capabilities.
What sets Auros apart is their flat organizational structure, offering significant autonomy and the opportunity to bring your ideas to life. You'll be working with sophisticated pricing models and state-of-the-art execution capabilities, helping to shape the systems that will power the business into the future.
The ideal candidate will have extensive experience with Python, distributed databases, and large-scale data pipelines. You'll be responsible for developing and maintaining high-throughput data architectures, implementing monitoring systems, and creating tools for automated pipeline management. Experience with technologies like Clickhouse, Hadoop, Snowflake, and cloud services is highly valued.
This role offers the chance to make a substantial impact on business outcomes through your daily work, collaborating with experienced trading teams and supporting systems that execute millions of trades on crypto exchanges globally. If you're passionate about data engineering in a fast-paced trading environment and want to work at the forefront of digital asset trading, this role at Auros presents an exceptional opportunity for career growth and technical challenge.
Responsibilities For Data Engineer
- Develop, test and maintain high throughput, high volume distributed data architectures
- Analyze, define and automate data quality improvements
- Develop and maintain real time data collectors for time series databases
- Build and improve trading analytics systems
- Create tools to automate the configuration, deployment and troubleshooting of the data pipeline
- Develop strategies to make our data pipeline efficient, timely and robust in a 24/7 trading environment
- Implement monitoring that measures the completeness and accuracy of captured data
- Manage the impact that changes to trading systems and upstream protocols have on the data pipeline
- Back populate and clean historical datasets
- Collaborate with traders and trading system developers
- Develop tools, APIs and screens to provide easy access to the archived data
Requirements For Data Engineer
- Extensive experience using Python for data analysis and time series data sets
- Experience with developing real time large scale data pipelines with petabytes of data
- Experience with distributed, high performance SQL and NoSQL database systems
- Bachelor's degree or above in Computer Science, Software Engineering or similar with excellent results
- Experience with data lakes, Amazon S3 (preferred)
- Experience developing in C++ on Linux (preferred)
- Protocol level network analysis experience (preferred)
- Experience with terraform (preferred)
- Experience with Clickhouse (preferred)
- Experience with Hive, Hadoop, Snowflake, Presto or similar (preferred)
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