The Finance Data Insights Release Management team provides change governance and release execution across Finance data products that support internal financial reporting and external regulatory reporting. 

As an analyst on the release management team, you will support end-to-end planning and execution of change events across Finance data platforms (data warehouse/lake environments). A key expectation of this role is to improve release velocity, reliability, and stakeholder experience by driving automation, standardization, and AI-assisted ways of working (e.g., faster detection, triage, and investigation of data anomalies and release issues).

Job Responsibilities

• Support end-to-end release/change execution across Finance data platforms, covering both planned and ad hoc change events. This role supports releases that occur on weekends, based on release calendars and business needs.
• Support high-velocity, well-controlled change by ensuring governance, approvals, documentation, and evidence are completed without slowing delivery.
• Identify, assess, and escalate risks/issues with clear options, impacts, and mitigation plans; drive timely decision-making.
• Lead stakeholder management across the lifecycle—setting expectations, negotiating scope/timelines, and tailoring communications to varied audiences.
• Embed AI-assisted analytics and automation into release execution and quality controls to accelerate anomaly detection, regression testing, issue triage, and root-cause investigation.
• Establish and track operational KPIs (e.g., release lead time, change failure rate, defect leakage, rework, incident volumes, automation coverage) and use insights to prioritize continuous improvement.
• Partner with data engineering and platform to improve data quality monitoring, observability, and proactive risk identification ahead of releases.
• Drive efficiency and performance improvement across the release lifecycle by standardizing processes, reducing manual effort, improving cycle times, and increasing predictability (e.g., fewer defects, faster recovery, improved on-time delivery).
• Execute testing and quality activities, including regression testing and anomaly detection, to validate changes align with requirements and expected outcomes.
• Produce executive-ready materials (updates, KPIs, decision decks) to support leadership visibility and modernization priorities.
• Program-manage key initiatives and contribute to modernization efforts through disciplined planning, reporting, and delivery governance.

Required qualifications, capabilities, and skills

• A bachelor’s degree
• 2+ years of experience in release/change management, program/project management, or related delivery roles.
• Working knowledge of managing release/change events with strong attention to risk, controls, and stakeholder impact.
• Strong data analytics skills, including ability to query and analyze data  to support validation and issue investigation.
• Experience coordinating testing and quality validation (e.g., regression testing, reconciliations, data quality checks) and leading root-cause analysis.
• Stakeholder management skills (influencing, negotiation, expectation management) and strong data storytelling.
• Advanced skills in metrics, reporting, and presentation creation, including executive-level PowerPoint outputs.
• Strong written and verbal communication, with ability to tailor messages by audience.
• Advanced Excel (or equivalent analytical tooling).
• Experience using AI-assisted analytics tools and/or automation to accelerate delivery and improve performance (e.g., anomaly detection, regression testing acceleration, smarter alerting/triage, faster investigation and root-cause analysis, improved data quality monitoring).

Preferred qualifications, capabilities, and skills

• Agile delivery mindset; experience using JIRA and working knowledge of JQL.
• Experience in Financial Services and/or a Consulting background.
• Experience with modern data platforms and tooling, including Databricks.
• Familiarity with Data Mesh concepts and/or cloud strategy.