Senior Data Analyst

Role Summary:
This role is part of the Consumer Data Team for a US Banking Client and focuses on ensuring the accuracy, consistency, and usability of data flowing to downstream Mnemonic systems. The position involves mapping fields, analyzing data quality, identifying gaps and discrepancies, and collaborating with business and technology teams to ensure reliable and well-understood data for decision-making.

Key Responsibilities:

• Explore, analyze, and profile data from multiple applications to assess structure, content, and quality.
• Identify data gaps, anomalies, and quality issues, and support root cause analysis to recommend corrective actions.
• Map data fields and attributes between source and target applications to ensure consistency and accuracy in data flows.
• Validate data from upstream applications and confirm alignment with downstream Mnemonics
• Partner with business and technology stakeholders to understand requirements, define validation rules, and recommend remediation steps.
• Document business and data requirements, maintain data dictionaries, and track data lineage for transparency.
• Monitor and report data quality metrics, communicating findings and recommendations to stakeholders.

Qualifications:

• Bachelor’s/Master’s degree in Business, Information Systems, or a related field with 4–7 years of experience in data or business analysis.
• Strong analytical and problem-solving skills with proficiency in SQL; familiarity with PySpark required
• Solid understanding of data profiling, validation, and quality management concepts.
• Experience collaborating with cross-functional teams across business and technology functions.
• Exposure to Banking or Financial Services domains preferred.
• Familiarity with MongoDB, or similar data platforms is an advantage but not necessary.

Key Responsibilities:

• Explore, analyze, and profile data from multiple applications to assess structure, content, and quality.
• Identify data gaps, anomalies, and quality issues, and support root cause analysis to recommend corrective actions.
• Map data fields and attributes between source and target applications to ensure consistency and accuracy in data flows.
• Validate data from upstream applications and confirm alignment with downstream Mnemonics
• Partner with business and technology stakeholders to understand requirements, define validation rules, and recommend remediation steps.
• Document business and data requirements, maintain data dictionaries, and track data lineage for transparency.
• Monitor and report data quality metrics, communicating findings and recommendations to stakeholders.

Bachelor's/Master's in any stream 5-8 years