Lead Market Data Developer

Summary

In details, the position encompasses duties and responsibilities as follows:

As a Senior market data developer, you will be responsible for developing market data capabilities ensuring reliable and accurate data feeds consumption and distribution. You will advance the development of our DMS aimed to ensure market data reliability for the Marketing Division’s operations.

The ideal candidate disposes of:

1. Own end to end market data development projects, from requirements gathering with business users, designing the solution with the team, building and delivering services for data parsing and distribution.
2. Deliver and enhance data parsers and other data processing mechanisms aligned to a standardised data consumption/distribution model. Steward ETL coding standards: ensuring that code is standardised, self-documenting and can be reliably tested.
3. Lead a team of market data professionals on development projects.
4. Act as SME for market data related initiatives and projects.
5. Provide second line of support for the daily parsing, internal assessments computations and delivery processes of market data.
6. Communicate with technical teams both within Glencore and external data providers such as financial exchanges, RPAs, etc.

Skills:

1. Deep understanding of market data, how it is onboarded and processed to be delivered to customers.
2. Experience in design and development of market data within data management system implementations.
3. Experience in delivery of data applications and services to automate business processes, meeting user functional requirements with high quality.
4. Driven to meet data management standards on performance, availability, scalability, security, integrity, among others.
5. Understanding and experience of tooling and technology that support all aspects of the Data solutions development lifecycle in an agile environment.
6. Detailed working knowledge of ETL/ELT, data warehousing methodologies and best practices including dealing with EOD and tick data.
7. Knowledge of different schema structures & design.
8. Deep understanding of deployment and automation workflows.
9. Knowledge in containerisation (Docker) and Databricks deployment is a plus.

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