Job purpose:

The Data Remediation and DaaS specialist will be responsible for improving customer data quality through various internal data remediation methodologies. This role will also focus on designing, implementing, and maintaining global and local data marts on the Bank's Data Lake to support business, marketing, credit & risk, analytics, regulatory, and other functional use cases. This role is crucial in ensuring high-quality customer data while enabling business functions with reliable and well structured data marts. The ideal candidate will be someone with a passion for data quality, strong technical skills, and a strategic mindset to drive data-driven decision-making across the Bank.

Key skills:

Engage with multiple business, product, credit, risk, analytics, marketing, finance, BIU etc. stakeholders to discover requirements of data marts alongwith the current challenges faced

• Drive for results and tangible outcomes

• Self-starter, having strong attention to detail and problem solving skills

• Strong knowledge of data quality frameworks, data cleansing, and remediation techniques

• Proficiency in SQL, Python, or other data manipulation languages

• Experience with ETL tools, data lakes, and data warehousing solutions

• Understanding of data modeling and database design

• Knowledge of data governance, compliance, and regulatory reporting requirements

• Experience with data visualization and reporting tools (Tableau, Power BI, etc.)

• Effective stakeholder management with cross-functional teams

• Strong analytical and problem-solving

4 years to 8 years of total work experience in Data Mart / Pipeline / Analytics creation

• Experience in Banking and Financial services

• Experience of working in large, multi-functional, matrix organization

• Strong technical & functional understanding of Data Remediation and Data Products that includes Staging, Mapping, Cleanse Function, Match Rules, Validation, Trust Scores, Remediation Techniques, Mart creation methodologies & best practices

• Experience with industry-leading reference & master data/metadata/data quality suites

• Exposure of working with Datalake & Cloud environment will be an added advantage

Data As Service Analyst