My client is looking to hire a visionary, strategic, and results-driven Chief Data Officer (CDO) to spearhead our enterprise data strategy.

Reporting directly to the Chief Technology Officer (CTO), the CDO will be responsible for architecting, scaling, and managing the companys data ecosystem.

This pivotal role owns the vision and execution for Data Engineering, Data Warehousing, Data Lakes, and Advanced Data Analytics to drive business growth, optimize risk management, and foster a truly data-driven culture across our financial services portfolio.

Core Responsibilities :

1. Data Strategy & Governance :

2. Data Engineering & Infrastructure :

- Oversee the design, construction, and maintenance of scalable data pipelines (ETL/ELT) to ingest structured and unstructured data from diverse financial systems.

- Modernize and manage the Enterprise Data Warehouse (EDW) and Data Lake / Lakehouse architectures to support real-time and batch processing.

- Collaborate with the CTOs core infrastructure and cloud teams to ensure seamless integration, high availability, and cost-optimized cloud data platforms.

3. Analytics & Business Intelligence :

- Lead the Data Analytics team to deliver actionable insights, predictive modeling, and advanced business intelligence (BI) dashboards for business units (Retail Loans, Wealth Management, Risk, Collections, etc.).

- Champion the adoption of Machine Learning (ML) and Artificial Intelligence (AI) use cases to enhance credit scoring, fraud detection, and customer personalization.

- Democratize data access across the organization by implementing self-service analytics tools.

4. Leadership & Stakeholder Management :

- Build, mentor, and lead a high-performing team of data engineers, data scientists, analysts, and database administrators.

- Act as a strategic partner to business heads, translating complex business problems into data-driven solutions.

- Manage relationships with external vendors, cloud service providers, and tool ecosystem partners.

Key Requirements & Qualifications :

Experience :

- 15+ years of experience in Data Management, Technology, or Analytics, with at least 5+ years in a senior leadership role (e.g., Head of Data, VP of Data Engineering).

- Strong background in the Banking, Financial Services, and Insurance (BFSI) sector is mandatory, with deep domain knowledge of lending systems, credit risk, and financial regulations.

Technical Expertise :

- Proven track record of building and managing modern data stacks, Data Lakes, and Warehouses (e.g., Snowflake, Databricks, AWS Redshift, Azure Synapse, or Google BigQuery).

- Deep understanding of data engineering frameworks (Hadoop, Spark, Kafka, Airflow) and relational/NoSQL databases.

- Familiarity with advanced analytics tools and languages (SQL, Python, R, PowerBI, Tableau).

Education & Leadership Skills :

- Bachelors or Masters degree in Computer Science, Data Science, Information Technology, Statistics, or a related field. An MBA is a plus.

- Exceptional communication and stakeholder management skills, with the ability to bridge the gap between complex technical concepts and business outcomes.

- A strong architectural mindset with the ability to balance long-term technical debt with short-term business delivery.