Chief Data Architect

About Rimes is a leading provider of enterprise data management solutions to the global investment community. We are driven by our passion for solving complex data problems and providing accurate information and industry-leading technology to our clients.

Position Overview:

We are seeking a Data Engineer to join our Data Engineering Team. As a Data Engineer, you will play a key role in modelling and developing our data platform. You will work closely with senior engineers to ingest, process, and ensure the quality of financial data using modern data tools and platforms such as Snowflake and Databricks.

Key Responsibilities:

• Data Pipeline Development: Assist in building and maintaining data pipelines to ingest and process financial data efficiently and reliably.
• End-to-End Ownership: Supported by seniors engineer and financial experts, take a holistic, end-to-end approach, ensuring smooth materialization from data ingestion through to querying. Understand the entire lifecycle of data processing and optimize for performance and reliability.
• Tooling and Automation: Support the development of tools that automate data ingestion and quality checks, helping to reduce manual work.
• Data Modeling: Learn to design and implement scalable data models under the guidance of senior engineers.
• Hands-On Development: Write clean, maintainable code data pipeline code in Python, Spark and SQL, and participate in code reviews and testing.
• Operational Support: Help monitor data workflows and troubleshoot issues to ensure smooth operation.
• Collaboration: Work closely with cross-functional engineer teams including Software, DevOps, Data Quality, Product, as well as our Operations team to understand data requirements and deliver solutions.
• Learning and Development: Continuously build your knowledge of data engineering best practices, financial data standards, and modern data platforms.

Qualifications:

Experience:

• 4+ years of experience in data engineering, with a focus on designing and building scalable data pipelines, ETL processes, and data modeling.
• Hands-on experience with large-scale distributed systems, data engineering, and cloud-native technologies.

Technical Skills:

• Proficiency in Python is essential. Experience with other programming languages such as Perl and C# is highly advantageous.
• Experienced with cloud-based data processing platform (DataBricks, Snowflake) and data transformation frameworks/engine (e.g., Apache Spark, Python Pandas)
• Deep understanding of data engineering concepts, including ETL, data flow, and data orchestration.

Benefits:

• A chance to make a tangible impact on the direction of our platform and business.
• Work with a talented, motivated team of engineers in a fast-paced, high-growth environment.
• Flexible remote work opportunities.
• Competitive salary and benefits.
• Supportive company culture focused on growth, innovation, and professional development.

Join us in revolutionizing financial data technology.