Location: Noida
Reports To: Head – Data & Analytics / CTO
Job Summary
The Business Intelligence (BI) Lead will drive the design, development, and governance of enterprise-wide BI solutions, data platforms, and analytics initiatives. The role requires deep expertise in Data Warehousing, Data Lakes, Snowflake, Data Security/Data Breach management, and the ability to leverage AI/ML and emerging technologies to strengthen organizational intelligence. The BI Lead will guide a team of data engineers, BI analysts, and developers to deliver scalable, secure, and high-performing data solutions supporting business growth and digital transformation.
Key Responsibilities
1. Strategy & Leadership
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Lead the BI function and define the roadmap for enterprise data architecture, analytics platforms, and modernization initiatives.
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Partner with business, technology, and leadership teams to translate strategic goals into data-driven insights and solutions.
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Drive adoption of advanced BI, predictive analytics, and AI-driven decision systems across functions.
2. Data Warehousing & Data Architecture
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Architect, implement, and optimize enterprise Data Warehouses and Data Lakes, ensuring scalability, performance, and efficient data modeling.
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Lead migration and modernization initiatives using Snowflake, cloud data warehouses, and modern ETL/ELT frameworks.
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Define and enforce best practices for data integration, data modeling, metadata management, and master data management.
3. Data Engineering & Platform Management
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Oversee development of end-to-end data pipelines using tools such as Informatica, Talend, dbt, Python, Airflow, Fivetran (as applicable).
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Ensure high data quality, data availability, and platform performance through rigorous governance and automation.
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Lead Cloud Data Platform strategy in collaboration with cloud teams (AWS/Azure/GCP).
4. Data Breach, Security & Governance
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Implement and oversee data security frameworks, data privacy controls, and breach detection systems across all BI platforms.
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Collaborate with InfoSec to ensure compliance with regulatory standards (ISO, GDPR, DPDP, SOC2).
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Establish robust data access controls, auditing, encryption standards, and incident response guidelines.
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Lead risk assessments, vulnerability checks, and remediation for BI systems.
5. Business Intelligence, Reporting & Visualization
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Drive development of dashboards, reports, self-service BI tools, and analytics portals using tools such as Power BI, Tableau, or Looker.
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Work with business teams to define KPIs, metrics, and performance frameworks.
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Promote data democratization and empower stakeholders with actionable insights.
6. AI/ML & Advanced Analytics
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Identify opportunities to integrate AI/ML models into the BI ecosystem for forecasting, anomaly detection, optimization, and automation.
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Collaborate with data scientists to operationalize advanced analytical models.
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Lead pilot programs on new technologies such as GenAI, RPA, NLP, MLOps and scale successful POCs across the organization.
7. Team Leadership & Project Delivery
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Manage a cross-functional BI and Data Engineering team, providing mentorship, technical guidance, and performance leadership.
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Drive Agile-based project execution for BI/analytics initiatives.
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Ensure timely delivery of high-impact data products while maintaining quality and security standards.
Required Qualifications & Experience
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Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Engineering, or related field.
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8–14 years of experience in BI, Data Warehousing, and enterprise analytics platforms.
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Strong hands-on expertise with Snowflake, Data Lake architectures, and large-scale data engineering pipelines.
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Proven experience in Data Breach management, cybersecurity alignment, and data protection frameworks.
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Deep knowledge of SQL, ETL/ELT frameworks, cloud platforms (AWS/Azure/GCP), and BI tools.
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Experience working with or implementing AI/ML platforms, predictive models, or GenAI technologies.
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Strong understanding of data governance, compliance, and privacy standards.
Preferred Skills
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Certifications in Snowflake, AWS/Azure Data Engineering, Power BI/Tableau, or AI/ML.
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Experience with microservices, APIs, and real-time analytics streaming tools (Kafka/Databricks).
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Hands-on Python and automation skills.
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Prior experience in energy, manufacturing, engineering, or high-scale technology environments (preferred but not mandatory).
Key Competencies
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Strong analytical and problem-solving skills.
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Ability to translate complex data concepts into business language.
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Strong leadership, stakeholder management, and communication skills.
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Innovation mindset with passion for new technologies and digital transformation.
