Data Engineering Lead

About BitMEX

BitMEX was one of the first crypto exchanges for derivatives. It exists to provide institutional and professional traders with a platform that caters to their needs.

BitMEX created the Perpetual Swap, the most popular crypto trading product in history. It is the only major global exchange that continues to create new cryptocurrency derivative products, most recently, the ETH Staking Swap. 

On BitMEX, users can trade cryptocurrency derivatives on a professional trading platform that provides low latency, deep liquidity and constant availability.  Since 2014, no cryptocurrency has been lost through intrusion or hacking, allowing BitMEX users to trade safely in the knowledge that their funds are secure. Spot trading is also supported, as well as the purchase and conversion of cryptocurrency - BitMEX supports 45+ derivatives contracts, 11 pairs for spot trading and the ability for users to convert 30+ cryptocurrencies. 

We are looking for individuals who are determined, responsible and collaborative to join BitMEX as we continue to build a thriving cryptocurrency ecosystem. We value attention to detail, speed and simplicity. As a global business operating a 24/7 exchange, we seek out those who are adaptable and can work across markets. 

For more information on BitMEX, company initiatives and our products, please visit the BitMEX Blog or www.bitmex.com, and follow LinkedIn, Discord, Telegram and Twitter.

Overview 

The Data Engineering team is part of the broader DevOps department, and sits at the core of the business,  bridging the fast-paced and never-ending data feeds from the BitMEX trading platform to the entirety of the firm. Whether it is about business development, financial products, risk management, compliance & market surveillance, marketing – consistent and reliable data is key, making Data Engineering the cornerstone to the firm’s success.

Responsibilities

• Design and maintain enhancements to our data warehouse, data lake, and data pipelines to increase their reliability and consistency
• Improve queriability of large historical datasets through industry-standard tools, careful data representation and aggregation for both technical and business units
• Ensure data governance and security/retention policies can be implemented and enforced
• Ensure that operational system integrations driven from the data stack are running, monitored and available
• Continually review the data platform to ensure that it is fit for purpose and meeting the needs of the business
• Support and maintain downstream integrations from our data lake, for example business intelligence and visualization tools and third party systems

Qualifications

• Experience in the data engineering field with demonstrated design and technical implementation of data warehouses
• Experience with OLAP databases, how they differ from OLTP databases, and data structuring/modeling with understanding of key data points in a business sense for trade-offs between storage/performance and usability
• Experience with building, deploying, and troubleshooting reliable, idempotent and consistent data pipelines working with disparate in-house and external data-sources, e.g. using Airflow DAGs
• Experience with AWS Redshift, Glue Data Catalog, S3, PostgreSQL, Parquet, Iceberg, Trino, and how they are managed using Terraform & Kubernetes
• Experience with data loading, extraction, manipulation and preparing data for ingestion and integration with visualization platforms such as Tableau.

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