Data Architect

About Keyrock

Since our beginnings in 2017, we've grown to be a leading change-maker in the digital asset space, renowned for our partnerships and innovation. 

Today, we rock with over 180 team members around the world. Our diverse team hails from 42 nationalities, with backgrounds ranging from DeFi natives to PhDs. Predominantly remote, we have hubs in London, Brussels, Singapore and Paris, and host regular online and offline hangouts to keep the crew tight.

We are trading on more than 80 exchanges, and working with a wide array of asset issuers. As a well-established market maker, our distinctive expertise led us to expand rapidly. Today, our services span market making, options trading, high-frequency trading, OTC, and DeFi trading desks.

But we’re more than a service provider. We’re an initiator. We're pioneers in adopting the Rust Development language for our algorithmic trading, and champions of its use in the industry. We support the growth of Web3 startups through our Accelerator Program. We upgrade ecosystems by injecting liquidity into promising DeFi, RWA, and NFT protocols. And we push the industry's progress with our research and governance initiatives. 

At Keyrock, we're not just envisioning the future of digital assets. We're actively building it.

Position Overview

The Data Architect is responsible for designing, implementing, and maintaining an organization's data architecture and strategy, ensuring that data is collected, stored, and processed efficiently and securely to support business intelligence, data analytics, and machine learning operations (MLOps) practices.

Key Responsibilities

• Designing Data Architecture: Plan and implement a robust, scalable data architecture that integrates data from various sources and supports diverse analytical needs, while optimizing costs and meeting business requirements.

• Implementing Data Engineering Pipelines: Design and develop data pipelines for data extraction, transformation, and loading (ETL) processes, ensuring data quality and consistency.

• Enabling Data Intelligence and Analytics: Build and maintain data warehouses, data marts, and data lakes to support business intelligence and data analytics initiatives.

• Supporting MLOps Practices: Collaborate with data scientists and machine learning engineers to design and implement data infrastructure and processes that support machine learning model development, deployment, and maintenance.

• Ensuring Data Security and Compliance: Implement security measures, policies, and procedures to safeguard data privacy and comply with relevant regulations.

• Data Governance and Management: Establish and enforce data governance policies and standards to ensure data quality, integrity, and accessibility.

• Collaborating with Cross-Functional Teams: Work closely with data engineers, data scientists, business analysts, and other stakeholders to understand data requirements and translate them into technical solutions.

• Staying Abreast of Technological Advancements: Keep up-to-date with emerging technologies and trends in data architecture, data engineering, and MLOps to identify opportunities for improvement and innovation.

• Optimizing Data Performance: Monitor and analyze data processing performance, identify bottlenecks, and implement optimizations to enhance efficiency and scalability.

• Documentation and Knowledge Sharing: Create and maintain comprehensive documentation of data architecture, models, and processing workflows.

Technical Requirements

• Extensive experience in data architecture design and implementation.

• Strong knowledge of data engineering principles and practices.

• Expertise in data warehousing, data modelling, and data integration.

• Experience in MLOps and machine learning pipelines.

• Proficiency in SQL and data manipulation languages.

• Experience with big data platforms (including Apache Arrow, Apache Spark, Apache Iceberg, and Clickhouse) and cloud-based infrastructure on AWS.

Education & Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent experience.

• Preferred certifications (optional):

  • AWS Cloud Data Engineer

  • AWS Machine Learning Ops Engineer

Leadership & Collaboration

• Passion for building scalable, reliable, and secure systems in a fast-paced environment.

• Ability to translate complex technic