Lead Data Scientist - Data Management
- Quantium Analytics
- 8 - 13 years
- Hyderabad
- 1 month ago
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Job Description
Role Summary
Join Quantiums India leadership team in shaping the future of data-drive business operations. The Data Systems Lead (India) is pivotal in executing Quantium's internal data and systems transformation strategy, working as part of a globally distributed team to ensure our corporate data ecosystem supports business growth and operational excellence. This role will lead and develop the India-based analytics operations team, working closely with the Australia-based leadership team to deliver high-quality data integration, system maintenance, and analytical solutions across Quantium's internal systems ecosystem.
The successful candidate will combine strong technical analytics engineering capabilities with stakeholder management skills, enabling them to work autonomously with business stakeholders when requirements need clarification whilst maintaining close collaboration with the Australian leadership team. This role is critical to Quantium's India growth strategy, building local capability whilst maintaining global standards and connectivity.
The position is designed to support both professional excellence and personal fulfilment, with flexible working arrangements and a commitment to inclusive leadership development.
Key Responsibilities
Team Leadership & Talent Development
- Guide and develop a team of 3-5 analysts focused on internal data systems and operations
- Recruit and nuture local India talent, including analysts similar to current team members
- Foster a culture of continuous improvement and operational excellence within the India operations team
- Partner closely with Australian squad leaders on resource planning and capability development
Data Systems & Analytics Engineering
- Execute and enhance data integration strategies across Quantium's internal systems ecosystem (Kantata, HubSpot, Anaplan, HRMS, Finance systems)
- Orchestrate ETL processes, data quality monitoring, and system maintenance operations
- Ensure data consistency and integrity across the corporate data warehouse
- Drive automation of manual processes and implement operational efficiencies
Stakeholder Engagement
- Collaborate with Australian leadership team to understand and translate business requirements
- Engage directly with internal business stakeholders across verticals when requirements need clarification
- Participate actively in regular forums with Finance, People & Culture, and vertical teams to gather feedback and requirements
- Support change management initiatives related to systems transformation
Operational Excellence
- Coordinate day-to-day operations of internal data systems and reporting processes
- Monitor and resolve data quality issues, implementing systematic approaches to problem-solving
- Support month-end financial processes, management reporting, and compliance requirements
- Maintain adherence to Quantium's data governance and security standards
Key activities
Strategic Execution
- Execute business plans for foundational internal data assets including corporate data management, system integrations, and operational reporting
- Support the development of the internal data and systems roadmap based on business requirements
- Coordinate with global teams on system enhancements and new implementations
Team Management
- Recruit and develop local analytics talent with strong ETL and data integration capabilities
- Create development plans and objectives aligned with operational excellence and business support objectives
- Provide coaching and mentorship to develop team members' technical and stakeholder management capabilities
- Build inclusive teams that leverage diverse perspectives and experiences
- Manage resource allocation across multiple internal projects and business-as-usual operations
Technical Delivery
- Oversee technical designs for data integration solutions and system enhancements
- Ensure quality standards are maintained across all data processes and deliverables
- Champion best practices for analytics engineering and data operations
- Support troubleshooting and resolution of complex data and system issues
Qualifications
Essential Requirements
- Analytics Engineering Foundation: Strong experience in ETL development, data integration, and analytics engineering practices
- Enterprise Systems Knowledge: Previous experience working with ERP systems, enterprise applications, or corporate data ecosystems
- Team Leadership and Development: Proven experience managing and developing analytics teams (3+ people)
- Data Integration Expertise: Strong understanding of data structures, data transformation, and system integration patterns
- Stakeholder Partnership: Demonstrated ability to work with business stakeholders and translate requirements into technical solutions
- Cross-cultural Communication: Comfort working across time zones and cultural contexts
Highly Desirable
- Experience with enterprise applications such as Kantata (or similar PSA tools), HubSpot, Anaplan, or HRMS systems
- Background in finance or HR data management and reporting
- Experience in professional services or consulting environments
- Previous experience working in globally distributed teams
- Understanding of data governance and compliance requirements
- Experience mentoring and developing junior team members
Skills Required
- Data Engineering: Proficiency in SQL, data transformation tools, and ETL processes
- Analytics Tools: Experience with data analysis and reporting tools
- System Integration: Understanding of API integrations and data warehouse concepts
- Problem Solving: Strong systematic approach to troubleshooting data and system issues
- Data Quality: Experience implementing data quality monitoring and improvement processes
Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: Data Science & Analytics
Role Category: Data Science & Analytics - Other
Role: Data Science & Analytics - Other
Employement Type: Full time
Contact Details:
Company: Quantium AnalyticsLocation(s): Hyderabad
Keyskills: Data Quality Strong Stakeholder Management ETL Maintenance Foundational Analytics SQL Data Science Team Management Data Manipulation Data Warehousing Data Integration Python
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