DataOps Engineer

Responsibilities:

• Create and manage toolkits frameworks for regulatory data analysis, development, testing and implementation.
  
  
• Analyse regulatory data requirements and understand regulatory problem statements.
  
  
• Mapping data to regulatory frameworks and policies.
  
  
• Design, develop, maintain, and optimise controls to monitor, report, and remediate regulatory data integrity (timeliness, completeness, accuracy) risks and issues particularly reconciling, reporting and remediating data incompleteness.
  
  
• Design, develop, maintain and optimise regulatory data delivery pipelines.
  
  
• Automating regulatory data management processes such as extraction, transformation and load.
  
  
• Contributing to the Enterprise Data Strategy and embedding it into the Regulatory Data deliverables.
  
  
• Supporting the Enterprise Data Strategy DevOps team where required.
  
  
• Ensure data security requirements are fully met.
  
  
• Effective collaboration with upstream, horizontal, and downstream teams.
  
  
• Senior stakeholder management.
  
  Experience / Competences:
  
  
• Essential Proficiency in writing database queries using SQL and general understanding of relational databases, and in data pipeline design and development.
  
  
• Experience with ETL processes, familiarity with the AWS ecosystem e.g., S3, Glue, DMS, CLI, etc., and experience with tools such as Qlik sense, PowerBI, or equivalent.
  
  
• Ability to setup database connections and manage related issues.
  
  
• Familiarity with data analysis on trading platforms to understand order and trade lifecycle events.
  
  
• Be able to work through, with completeness and accuracy, a technical checklist of data validation and feed the results back to the Data Lead Be able to understand the reconciliation approach of order and order event count matching and use analysis techniques to identify differences and their cause.
  
  
• Self-starter, strong problem solver and great attention to detail.
  
  
• Excellent written and verbal communication.
  
  
• Adaptable, resilient, and a forward thinker. Knowledge of data security best practices.
  
  Desired:
  
  
• DataOps / data pipeline output testing experience
  
  
• Familiarity with GDPR, MAR, MiFID, and WORM regulations.
  
  
• Willingness to learn new technologies.
  
  Project:
  
  
• Migration of datasets (schema evolution).
  
  
• To be responsible for providing technical guidance to a team of developers, enhancing their technical capabilities and increasing productivity.
  
  
• To conduct comprehensive code reviews, establish and oversee quality assurance processes, performance optimization, implementation of best practices and coding standards to ensure successful delivery of complex projects.
  
  
• To ensure process compliance