Pay Rate Range: $ 56.81 - 58.33/hr.Job Title: Sr Business Data Consultant
Job Description:Key Responsibilities
• Data Analysis & Insight Generation: Perform in-depth analysis of enterprise
data to uncover trends, patterns, and correlations. Identify actionable insights
and data-driven opportunities that inform decision-making and strategic
initiatives.
• Data Use Case Identification: Collaborate with stakeholders to identify and
define data use cases across functional domains, ensuring alignment with
business priorities and future-state data strategy.
• Business-to-Technical Translation: Engage with stakeholders to translate
business requirements into clear technical specifications, analytical models, and
actionable deliverables.
• Impact Assessment: Analyze current-state data and infrastructure versus
future-state goals; identify data and process gaps; define mitigation strategies.
• Data Profiling & Quality Analysis: 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.
• Data Integration & Transformation: Design and validate data pipelines and
transformations; document lineage and dependencies.
• Feature Engineering & Analytics: Use Python and SQL to extract, clean, and
engineer data features for analytics and modeling.
• AI-Assisted Analytics: Apply basic AI/ML and LLM-based tools (e.g., promptbased
data exploration, AI-assisted feature engineering, or generative AI
copilots) to accelerate data analysis, documentation, and insight generation.
• Reporting & Visualization: Build and maintain insightful dashboards and
reports to communicate findings effectively.
• Governance & Documentation: Maintain business glossary, data dictionary,
and metadata aligned with governance standards.
• Testing & Validation: Participate in validation of new or transformed data sets to
ensure integrity and alignment with business requirements.
• Knowledge Management: Maintain the data dictionary and business glossary
for assigned domains, capturing and documenting definitions aligned with
business leadership and global teams.
• Cross-functional Collaboration: Partner closely with data engineers, product
managers, and business SMEs to align solutions with business objectives.
Required Skills & Qualifications
• 8–12 years of experience in data analytics, business analysis, or data
management.
• 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 dashboard 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) — no deep ML modeling expertise required.
• 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.
Environment & Tooling Stack
• SQL (PostgreSQL, Snowflake, Redshift)
• Python (Pandas, NumPy, feature engineering)
• AI for visualization
• Git / Bitbucket for version control
• JIRA / Confluence for project tracking and documentation
Experience Required: 8-10 years
| Skills: | | Category | Name | Required | Importance | Experience |
|---|
| SkillCategoryTest1_MN | Digital : Python | Yes | 1 | >7 years | |
|
|---|