Role & responsibilities

Team Leadership & Operations

- Lead, mentor, and develop a team of data engineers, analysts, integration engineers, PowerBI developers and AI/ML Engineers.
- Provide direction, coaching, and performance feedback to team members while supporting their career growth and technical development.
- Foster a culture of continuous improvement, collaboration, and innovation.
- Implement and maintain a comprehensive data strategy aligned with business goals.
- Manage intake, prioritization, and delivery of data-related requests, projects, and enhancements
- Establish SLAs, operational metrics, and reporting cadences to communicate team performance to leadership
- Manage resource planning, workload distribution, project delivery, hiring, onboarding and support activities across the data intelligence function
- Foster a collaborative, data-driven culture aligned with organizational goals and values
- Partner closely with cross-functional teams including ecommerce, Data Engineering, Business Insights, Enterprise Applications, Infrastructure, Security, and QA.
- Provide status updates to leadership on operational health, key issues, risks, priorities, and progress

Data Warehouse Management

- Oversee the design, development, and operational maintenance of the enterprise Data Warehouse architecture
- Manage data ingestion pipelines, ETL/ELT processes, and data transformation workflows
- Ensure data integrity, consistency, and availability across all warehouse environments (Dev, QA, Prod)
- Provide technical leadership in SQL development, ETL/ELT processes, data modeling, database design, and performance tuning.
- Evaluate and recommend current technologies, tools, and methodologies to enhance warehouse performance




- Support data warehouse enhancements, new data source onboarding, reporting needs, and business-critical data initiatives.
- Implement and enforce data quality controls, lineage, metadata management, and documentation.

API Integrations

- Lead the execution of API integrations connecting internal and third-party systems
- Collaborate with engineering and vendor teams to design, build, and monitor RESTful and SOAP API integrations
- Establish standards for API documentation, versioning, error handling, and data validation
- Drive improvements in integration support processes, incident response, and operational reliability.
- Partner with application, integration, ERP, ecommerce, and business teams to ensure APIs and data integrations are stable and functioning as expected.
- Assist to troubleshoot and resolve integration failures, ensuring minimal disruption to downstream systems and reporting

Analytics & Power BI

- Manage and support analytics requests related to Power BI reports, dashboards, datasets, and business reporting needs.
- Partner with business users to understand reporting requirements, data definitions, KPI needs, and analytics priorities.
- Champion self-service analytics by establishing best practices, data models, and certified datasets




- Provide training and enablement resources to empower business users across the organization
- Support report enhancements, dashboard issue resolution, and dataset refresh failures.
- Promote consistency in reporting, data definitions, and analytics best practices across the organization.

Data Governance & Security

- Lead the overall data intelligence strategy aligned with business priorities, technology roadmap, and enterprise goals.
- Partner with Security, Compliance, and Business teams to enforce data governance policies and access controls
- Ensure compliance with applicable data privacy regulations (e.g., GDPR, CCPA) and SOX/ITGC controls where applicable
- Manage audit readiness, change management, and segregation of duties across environments.
- Maintain comprehensive data dictionaries, lineage documentation, data cataloging, and metadata management practices

AI & Machine Learning

- Lead and support the organizations advancement into AI, machine learning, predictive analytics, and intelligent automation.
- Identify practical AI/ML use cases that can improve business outcomes, operational efficiency, customer experience, and decision-making.
- Partner with data scientists, engineers, analysts, and business teams to develop scalable AI/ML solutions.
- Help establish the foundation required for AI readiness, including clean data pipelines, governed datasets, quality controls, and reusable data assets.
- Support the evaluation and implementation of AI-enabled analytics tools, machine learning platforms, and automation capabilities.
- Promote responsible AI practices, including data privacy, model transparency, risk management, and ethical use of data.

📌 Associate Director, Data Intelligence (Ahmedabad)
🏢 RK HR Management
📍 Ahmedabad