Description

Role Overview:

The Sr Business Data Consultant will be responsible for performing in-depth analysis of enterprise data to identify trends, patterns, and actionable insights. This role involves collaborating with stakeholders to define data use cases, translating business requirements into technical specifications, and assessing the impact of data infrastructure changes. The consultant will leverage Python and SQL for data engineering, apply AI-assisted analytics, and build effective dashboards to communicate findings, ensuring data integrity and governance.

Key Responsibilities:

• Perform in-depth analysis of enterprise data to uncover trends, patterns, and correlations, identifying actionable insights and data-driven opportunities.
• Collaborate with stakeholders to identify and define data use cases across functional domains, ensuring alignment with business priorities and future-state data strategy.
• Engage with stakeholders to translate business requirements into clear technical specifications, analytical models, and actionable deliverables.
• Analyze current-state data and infrastructure versus future-state goals; identify data and process gaps; define mitigation strategies.
• Perform deep dives into structured and semi-structured datasets to assess completeness, consistency, and accuracy; work with SMEs to understand data availability and source gaps.
• Design and validate data pipelines and transformations; document lineage and dependencies.
• Use Python and SQL to extract, clean, and engineer data features for analytics and modeling.
• Apply basic AI/ML and LLM-based tools (e.g., prompt-based data exploration, AI-assisted feature engineering, or generative AI copilots) to accelerate data analysis, documentation, and insight generation.
• Build and maintain insightful dashboards and reports to communicate findings effectively.
• Maintain business glossary, data dictionary, and metadata aligned with governance standards.
• Participate in validation of new or transformed data sets to ensure integrity and alignment with business requirements.
• Maintain the data dictionary and business glossary for assigned domains, capturing and documenting definitions aligned with business leadership and global teams.
• Partner closely with data engineers, product managers, and business SMEs to align solutions with business objectives.

Required Skills:

• Advanced SQL expertise with ability to query and optimize large, complex datasets.
• Proficiency in Python for data analysis, transformation, and feature engineering (Pandas, NumPy).
• Experience with building dashboards using AI or similar visualization frameworks for data storytelling and dashboards.
• Deep understanding of data architecture, governance, MDM, and data lineage.
• Proven track record in identifying and scoping new data use cases and converting insights into business recommendations.
• Strong analytical thinking, stakeholder management, and communication skills.
• Basic working knowledge of AI/ML concepts and exposure to AI-assisted tools (e.g., Copilot-style coding assistants, LLM-based chat/analytics tools, or prompt engineering for data tasks).
• Experience with Snowflake, Databricks, or Hadoop/Spark environments.
• Exposure to data catalog or governance tools (Collibra, Alation).
• Familiarity with D&B data hierarchy, enrichment, or similar reference data systems.
• SQL (PostgreSQL, Snowflake, Redshift)
• Python (Pandas, NumPy, feature engineering)
• AI for visualization
• Git / Bitbucket for version control
• JIRA / Confluence for project tracking and documentation

Qualifications:

• 8–12 years of experience in data analytics, business analysis, or data management

Key Skills

Education

Any Graduate