Senior Data Analyst

JOB FUNCTION AND RESPONSIBILITIES:

Collaborate with business stakeholders to understand data needs and translate them into analytical and reporting requirements.

Design, create, and implement new data quality rules aligned with business and regulatory requirements.

Ensure data accuracy, consistency, and integrity through systematic validation, profiling, and quality checks.

Analyze source systems and datasets to identify patterns, anomalies, and data inconsistencies.

Build, optimize, and maintain SQL queries, views, and data models to support reporting and analytics.

Demonstrate strong proficiency in PL/SQL, including development of stored procedures and performance optimization.

Contribute to the definition and standardization of KPIs, metrics, and enterprise data governance standards.

Investigate data quality issues, perform root ‑ cause analysis, and recommend solutions for data standardization and remediation.

Develop and maintain data dictionaries and metadata documentation for Critical Data Elements (CDEs).

Respond to and resolve inquiries from the Data Stewardship mailbox, ensuring timely and accurate support.

Additional Responsibilities (AI / ML / LLM Focus)

Apply ML techniques for anomaly detection, classification, and predictive analytics.

Use Python for data analysis and automation

Support integration of AI/ML models into data pipelines and reporting

Leverage LLMs for data summarization, metadata enrichment, and natural language querying

Implement AI-driven data quality monitoring and intelligent rule generation

Contribute to AI-enabled analytics solutions for enhanced insights

QUALIFICATION:

Education: Bachelor’s/master’s degree in engineering/computer applications

Strong understanding of RDMBS databases such as Oracle and SQL Server

Good understanding of Business Intelligence tools such as MicroStrategy and Power BI

Expert proficiency in SQL for data extraction, manipulation, and analysis.

Solid understanding of database structures, data warehousing concepts, and data governance principles.

Proven ability to work independently, manage multiple projects, and prioritize effectively.

Exceptional analytical and problem-solving skills, with the ability to tackle complex business challenges and provide innovative solutions.

Hands-on experience with Python for data analysis and ML. Knowledge of ML algorithms (regression, classification, clustering)

Familiarity with LLMs (prompt engineering, embeddings, GenAI use cases)

Understanding of AI/ML lifecycle (data prep, modeling, evaluation, deployment)

WORK SCHEDULE OR TRAVEL REQUIREMENTS:

Mid Shift (2PM – 11PM), No Travel required.