Data Operations Engineer

Data Operations Engineer (12-month maternity cover)

Smart Data Foundry is unlocking the power of financial data to improve people’s lives.

As a Data Operations Engineer you will provide first‑line support to researchers, data scientists, and partners using our Trusted Research Environment (TRE). Your responsibilities include guiding users through TRE access procedures, troubleshooting data access and usability issues, and ensuring compliance with data governance and data quality standards.

Key Responsibilities

• Respond to user queries via the help‑desk system.
• Guide researchers through TRE access procedures and data navigation.
• Troubleshoot data access and usability issues.
• Liaise with system administrators and data providers to resolve user problems.
• Manage and verify user permissions for key data assets and infrastructure.
• Communicate timelines and potential solutions to internal and external stakeholders.
• Write and adapt command‑line code to perform data quality checks to ensure privacy standards are met before data is made available to researchers.
• Perform disclosure checks on research outputs prior to wider dissemination outside the secure environment.
• Execute data requests by running command‑line scripts and queries.
• Assess data usability and report quality issues to users and data partners.
• Maintain audit logs and compliance documentation.
• Support secure data transfer operations within the TRE.
• Identify opportunities to streamline user workflows and automate routine tasks.
• Create and update user guides and process documentation.
• Contribute to efficiency improvements in data ingress and egress procedures.

About You

• Ability to learn and adapt to utilizing UNIX command line.
• Strong problem‑solving skills and ability to develop processes within technical environments.
• Excellent verbal and written communication skills.
• Personable approach and ability to develop positive working relationships at all levels within an organisation.
• Self‑motivated, proactive, and able to work autonomously under pressure and with conflicting priorities.
• Willingness to learn data quality and management principles and routines.
• Ability to capture technical processes clearly and concisely in written format.
• Comfortable dealing with ambiguity and reacting quickly in an evolving fast‑paced environment.
• Ability to liaise with stakeholders to communicate timelines, potential improvements, and deal with user issues as an intermediary within the environment.