Data Analyst

Position Overview

As enterprise data becomes ever more crucial to operational efficiency and strategic direction, the Senior Data Analyst plays a central role in converting complex data assets into actionable intelligence. Working within the Data Services group, this position focuses on building scalable analytics solutions, tracking critical data quality indicators, and maintaining enterprise reporting frameworks across core master data domains—including Item, Customer, and Supplier domains.

In this role, you will interface directly with business leaders, data engineering teams, and MDM specialists to surface operational trends and establish data-driven decision frameworks. Utilizing modern analytics ecosystems—such as Databricks, cloud architectures, Informatica tools, and visualization suites like Tableau or Power BI—the position drives enhanced data governance, clearer operational visibility, and measurable business performance.

Key Responsibilities

BI Development & Dashboarding

• Build, refine, and sustain enterprise-level scorecards and interactive dashboards using Tableau, Power BI, or equivalent tools.

• Translate operational metrics, key trends, and data quality indicators into clear, intuitive visual reports.

• Establish self-service reporting capabilities to allow cross-functional teams direct access to insights.

• Gather requirements from business partners and convert them into robust, maintainable dashboard architectures.

• Validate reporting consistency and ensure strict alignment with organizational data standards and governance policies.

Advanced Analytics & Business Insights

• Execute exploratory and structured data analyses to pinpoint operational bottlenecks, trends, and growth opportunities.

• Define and maintain key performance indicators (KPIs) to track both operational efficiency and underlying data health.

• Lead root-cause investigations for data discrepancies and business process breakdowns.

• Provide data-backed recommendations and strategic analysis to support business initiatives and ad hoc executive requests.

Master Data & Quality Assurance

• Perform deep-dive analysis across primary master data domains (Supplier, Customer, Product/Item).

• Partner with Data Governance and MDM teams on profiling, validation, cleansing, and ongoing monitoring efforts.

• Design and deploy data quality scorecards to monitor record completeness, accuracy, timeliness, and consistency.

• Work alongside Data Stewards to troubleshoot and resolve data integrity issues at the source.

Data Platform & Engineering Collaboration

• Construct complex SQL queries and analyze large-scale datasets within Databricks and cloud-based warehouse environments.

• Coordinate with Data Engineers to verify data pipeline outputs, data models, and underlying reporting tables.

• Help define business logic, metrics definitions, and semantic layer architectures.

• Perform rigorous validation testing for new analytics tools, feature releases, and database updates.

Stakeholder Management & Enablement

• Engage cross-functional teams to understand operational needs and spot high-impact analytics opportunities.

• Present complex analytical findings, findings, and technical concepts clearly to both technical and non-technical stakeholders.

• Maintain complete documentation of metric logic, data definitions, calculation rules, and analytics workflows.

• Conduct user enablement sessions and offer ongoing support for deployed reporting solutions.

Core Qualifications

Education

• Bachelor’s degree in Computer Science, Information Technology, Data Analytics, Statistics, Mathematics, Engineering, Business Analytics, or equivalent practical experience.

Experience & Skills

Required:

• 3–5 years of professional experience in data analytics, business intelligence, or enterprise reporting.

• Demonstrated proficiency with BI visualization platforms (Power BI, Tableau, or similar).

• Strong hands-on SQL query writing and dataset analysis capabilities.

• Practical experience working with large-scale datasets sourced from varied enterprise systems.

• Proven ability to gather business specifications and translate them into functional technical deliverables.

• Background in developing KPIs, tracking performance metrics, and supporting data quality processes.

Preferred:

• Exposure to Master Data Management (MDM) frameworks and tools (e.g., Informatica MDM, Informatica IDQ).

• Experience using cloud-based data platforms and analytics environments (Databricks, Spark, AWS, Azure, or GCP).

• Familiarity with data governance practices, dimensional modeling, and data warehousing principles.

• Experience working within Agile project frameworks.

• Working knowledge of Python for automated data processing or exploratory analysis.

Technical & Core Competencies

• Visualization & Analytics: Power BI, Tableau, Advanced Excel, Data Storytelling, Dashboard Architecture, Performance Metrics/KPI Design.

• Data Engineering & Querying: SQL, Relational Databases, Databricks, Data Warehousing, Data Modeling Concepts, Data Quality Profiling.

• Preferred Tools: Informatica IDQ (Analyst/Developer), Informatica MDM, Delta Lake, PySpark/Python, Git, Azure DevOps.

• Core Strengths: Problem-solving, Root-Cause Analysis, Data Governance Awareness, Cross-Functional Collaboration, Statistical Interpretation.