Manager, Technology Consulting

Key Responsibilities: 
 

1. Flow Cell Leadership & Delivery Accountability 

• Lead and manage a cross-functional flow cell team comprising data managers and data engineers, ensuring clear ownership of work intake through to delivery. 

• Drive a flow-based delivery model, optimising work-in-progress (WIP), cycle times, and throughput across the team. 

• Ensure all client deliverables are completed on time, within SLA, and to defined quality standards. 

• Act as the primary escalation point for delivery risks, bottlenecks, and data-related issues impacting client outcomes. 

• Maintain clear visibility of pipeline, capacity, and delivery commitments through dashboards and reporting. 

2. Data Management Strategy & Process Governance 

• Implement and continuously evolve data management strategies, policies, and procedures aligned with organisational standards and client requirements. 

• Define and enforce data lifecycle processes (ingestion, validation, transformation, storage, and delivery). 

• Establish robust data governance frameworks, ensuring compliance with regulatory, contractual, and internal standards. 

• Maintain ownership of RAID logs for data-related risks and issues, ensuring clear documentation of business impact (e.g., revenue, delivery delays, reputational risk). 

3. Quality, Standards & Performance Management 

• Define and operationalise data quality standards, validation rules, and acceptance criteria. 

• Monitor and report on KPIs and SLAs, including:  

• Data quality and defect rates. 

• Cycle time / lead time. 

• Throughput and backlog health. 

• SLA adherence and client delivery metrics. 

• Implement proactive quality controls and root cause analysis processes to reduce recurring issues. 

• Drive continuous improvement initiatives to enhance efficiency and reduce manual intervention. 

4. Technical Oversight & Data Architecture Alignment 

• Oversee the design, development, and maintenance of databases, pipelines, and data warehouses supporting flow cell operations. 

• Ensure data solutions are scalable, secure, and aligned with enterprise architecture standards. 

• Partner with engineering and platform teams to optimise tools such as DRiVS, TREX, Data Forge, or equivalent systems. 

• Ensure appropriate use of automation, validation frameworks, and orchestration tools to improve data processing efficiency. 

5. Cross-Functional Collaboration & Stakeholder Management 

• Collaborate with product owners, client teams, and upstream/downstream stakeholders to define data requirements and priorities. 

• Translate business needs into clear, actionable data workflows and deliverables. 

• Act as a bridge between technical teams and business stakeholders, ensuring alignment on expectations, timelines, and quality. 

• Provide regular updates to leadership on delivery performance, risks, and improvement initiatives. 

6. Continuous Improvement & Flow Optimisation 

• Identify and remove bottlenecks within the flow cell using data-driven insights and process analysis. 

• Drive adoption of lean and flow-based principles, including:  

• Work standardisation. 

• Automation of repetitive tasks. 

• Reduction of handoffs and rework. 

• Lead process improvement initiatives focused on increasing throughput and reducing cycle times. 

• Champion innovation, including AI/ML-driven opportunities for data validation, enrichment, and workflow automation. 

7. People Leadership & Capability Development 

• Mentor, coach, and develop team members, fostering a culture of accountability, collaboration, and continuous learning. 

• Define clear roles and responsibilities within the flow cell, ensuring optimal skill utilisation and coverage. 

• Support career development, performance management, and succession planning across data management and engineering roles. 

• Promote a high-performance culture grounded in ownership, quality, and operational excellence. 

8. Risk, Compliance & Data Security 

• Ensure all data handling processes comply with relevant data protection regulations and organisational policies. 

• Manage risks related to data integrity, security, and client delivery commitments. 

• Implement audit-ready processes and documentation to support governance and compliance reviews. 

Success Measures (Indicative) 

• Consistent SLA achievement and improved client satisfaction. 

• Reduction in data defects and rework rates. 

• Improved cycle time and throughput across the flow cell. 

• Increased automation and reduced manual processing effort. 

• Clear, audit-ready governance and risk management practices. 
   

Basic Qualification: 

• Bachelor's degree in computer science, information technology, or a related field; advanced degree preferred. 

• Proven experience of 5 -7 years in data management with at least 2 years in a supervisory role, with a track record of leadership and project management. 

• Strong understanding of data management principles, methodologies, and best practices. 

• Proficiency in database technologies (e.g., ETL, SQL, SSIS, Python) and data management /warehousing concepts. 

• Experience with data modeling, data visualization, and business intelligence tools. 

• Excellent analytical and problem-solving skills, with the ability to analyze complex data sets and derive actionable insights. 

• Strong communication and interpersonal skills, with the ability to effectively collaborate with stakeholders. 

• Demonstrated leadership abilities, including team management, coaching, and performance evaluation. 

• Familiarity with data governance frameworks, regulatory requirements, and compliance standards. 

• Ability to work in a fast-paced, dynamic environment and manage multiple priorities effectively. 
   

Preferred Qualification: 

• Excellent organizational skills and ability to effectively handle multiple priorities. 

• Self-starter with ability to interface with people in a matrix type organization. 

• Knowledge of work measurement, and personnel development and training. 

• Technical understanding of implementing, configuration of software desired.