- The Director leads, scales, and optimizes the Global Master Data domains
- This position is responsible for delivery and governance, overseeing the development and support of data quality, governance, lineage, pipelines and products, infrastructure, and automation to ensure reliable, secure, and efficient data delivery
- The Director works with cross-functional teams to promote operational excellence and implement AI-enabled solutions for proactive issue resolution
- This role requires strong expertise in data platforms, leadership, process transformation, and the ability to communicate KPIs and strategic insights to senior leadership
- The Director manages multiple Associate Directors and Lead Consultants in delivering Global Master Data development and operations
- They are accountable for building high-performing teams, enabling data-driven decisions, and aligning enterprise data systems with changing business needs
What you'll be Responsible for:
- Team Leadership : Guiding and mentoring team while nurturing a collaborative environment that encourages innovation and creativity.
- Collaborating with key stakeholders to create a strategy that aligns seamlessly with overarching business objectives, ensuring the initiatives directly contribute to organizational success.
- Leadership Vision : Inspire and guide a high-performing team by setting clear goals, fostering accountability, and creating a culture of continuous improvement.
- Will be leading portfolio of around 50-60 associates and providing oversight to drive operational excellence by establishing best practices for data quality, governance, pipeline monitoring, automation, and incident management using AI/ML-enabled observability tools.
- Program Project Management : Leading projects from inception through deployment, ensuring adherence to quality standards and project timelines - a critical factor in maintaining stakeholder trust and satisfaction.
- Data Analytics Architecture Oversight : Crafting and implementing robust information architecture that facilitates effective integration, storage, and processing, thereby enhancing the organization s capabilities.
- Provide technical guidance and leadership for data availability, quality, reliability, and incident resolution; present key metrics and insights to senior leadership regularly.
- Performance Monitoring : Establishing and utilizing metrics to evaluate information processes and team performance, allowing for continuous improvement and optimization of engineering efforts.
- Define track success criteria and value measures for insourcing and knowledge transition from vendor partners.
- Enable Automation and AI first culture by reducing manual activities, repetitive incidents and streamlining issue resolution processes through smart alerting, auto-remediation, and orchestration enhancements.
- Ensure effective SLA adherence , capacity planning, change management, and risk mitigation across all critical data services.
- Mentor and grow talent within the team, conducting regular performance reviews, skill development planning, and succession pipeline development.
- Stay current with trends in AI for IT operations (AI/MLOps), SRE practices, and emerging technologies to future-proof data operations.
- Strategic Communication : Translate operational KPIs, risk metrics, and platform health insights into executive-ready updates that support strategic decisions.
- Quality Compliance Focus : Champion data quality, lifecycle management, and regulatory compliance (eg, HIPAA, GDPR) within operational processes.
- Innovation Scalability : Continuously evaluate tools, frameworks, and industry best practices to future-proof the data ecosystem and scale operations efficiently.
What You should Bring:
- Technical Proficiency : A deep understanding of data modelling, ETL processes, and warehousing technologies is essential.
- Collaborate with cross-functional functions such as Enterprise Data, Cybersecurity, Infra and Platform etc to align on priorities to meet commercial business demands.
- Analytical Skills : The capability to analyse intricate information sets and extract actionable insights is vital for the director of data engineering to drive informed decision-making within organizations.
- Communication Skills : Exceptional verbal and written communication skills are required to articulate information strategies effectively to non-technical stakeholders.
- Operational Mindset : Strong grasp of data SLAs/SLOs, incident response frameworks, observability tools (eg, Datadog, Grafana), and performance tuning in large-scale environments.
- AI Automation Focus :
Understanding of AIOps or automation tools and the ability to identify opportunities to apply AI for root cause prediction, cost optimization, and reducing manual workload. - People Process Skills :
Proven ability to lead diverse technical teams, mentor talent, and implement scalable processes for reliability, quality, and compliance.
Basic Qualifications and Experience Requirement:
- bachelors or masters degree in Computer Science, Information Systems, Data Engineering, or a related field.
- 15+ years of experience in data engineering, platform operations, or data infrastructure roles.
- Minimum 8 years of experience leading technical teams or managing global data operations.
- Proficiency in AWS, Data Bricks, data engineering practices, orchestration platforms and cloud services (AWS, Azure).
- Demonstrated experience in managing SLAs/SLOs, resolving production issues, and driving automation to reduce operational overhead.
- Exposure to AIOps or data operations automation practices is a strong plus.
Additional Skills/Preferences:
- Domain experience in healthcare, pharmaceutical ( Customer Master, Product Master, Alignment Master, Activity, Consent etc ), or regulated industries is a plus.
- Partner with and influence vendor resources on solution development to ensure understanding of data and technical direction for solutions as well as delivery
- AWS Certified Data Engineer - Associate
- Databricks Certified Data Engineer (Associate or Professional)
- AWS Certified Architect (Associate or Professional)
- Familiarity with AI/ML workflows and integrating machine learning models into data pipelines
Additional Information:
Business travel to the USA and other countries may be required for periods of 2-3 weeks, as needed (~2 times per year)
