Data Analyst

Role: Data Analyst

Location: Northampton (2-3 days on-site)

Duration: 6 months

Day rate: £410 per day inside IR35

Role Overview:

We are seeking a skilled Data Analyst to join our team and take responsibility for establishing and embedding data reporting and tracking across all Tech Debt activities within the Tech Sustain portfolio for our banking end-client. The role involves collation of technical debt data from various sources, validation with Tech Leads and Tech Debt Subject Matter Experts (SMEs) in engineering, and the creation of monthly reports for stakeholder consumption.

Key Responsibilities:

Collation of Technical Debt Data:

• Gather technical debt data from ELF (Enterprise Logging Framework), TLM (Transaction Lifecycle Management), Service Risk, and other relevant sources on a weekly basis.
• Ensure the accuracy and completeness of collected data.

Data Validation:

• Work closely with Tech Leads and Tech Debt SMEs in engineering to validate and verify technical debt data.
• Collaborate with stakeholders to address any discrepancies or issues identified during the validation process.

Monthly Reconciliation:

• Conduct monthly reconciliation of technical debt commitments made against actual progress.
• Generate comprehensive reports outlining progress, challenges, and recommendations for improvement.

Stakeholder Communication:

• Effectively communicate technical debt insights and progress to stakeholders in a clear and concise manner.
• Collaborate with cross-functional teams to address queries and provide additional context as needed.

Process Improvement:

• Identify opportunities for process improvement in data collection, validation, and reporting.
• Implement enhancements to streamline and optimize the Tech Debt tracking process.

Qualifications:

• Bachelor's degree in Data Science, Computer Science, Statistics, or a related field.
• Proven experience as a Data Analyst, preferably in a banking or financial services environment.
• Strong understanding of technical debt concepts and associated metrics.
• Proficiency in data analysis tools and programming languages (e.g., SQL, Python, R).
• Excellent communication skills with the ability to convey complex technical information to non-technical stakeholders.

Preferred Skills:

• Experience with ELF, TLM, and Service Risk data.
• Familiarity with banking and financial systems.
• Attention to detail and a commitment to data accuracy.
• Ability to work collaboratively in a cross-functional team environment.
• Strong problem-solving and critical-thinking skills.