Data Governance Data Analyst

Job: Data Governance Data Analyst Location: Easton, PA (Hybrid – 2 Days a Week Onsite) Duration: 6 Months Contract-to-Hire Experience: Ideally 4–6 years WORK ARRANGEMENT:

• Initial onboarding: 2 days per week onsite in Easton, PA during the first few months.
• After ramp-up: Approximately 2 days per month onsite once fully trained and comfortable in the role.
• Candidates must be local to Easton, PA, or within reasonable commuting distance.

POSITION OVERVIEW

• Client is seeking a detail-oriented, curious, and analytical Data Governance Data Analyst to support the quality, consistency, and understanding of enterprise data across multiple business systems.
• This is a hands-on Data Analyst position, not a traditional Business Analyst role. The ideal candidate will have strong SQL skills, experience investigating complex datasets, and an understanding of how data moves through enterprise systems, data warehouses, and reporting environments.
• This individual will work closely with business stakeholders, Data Engineering, and BI teams to trace data lineage, investigate discrepancies, document data relationships, and improve overall data quality and transparency.
• We are looking for someone who enjoys digging into data, asking questions, researching problems, and independently identifying solutions.

KEY RESPONSIBILITIES

Data Analysis & SQL:

• Write and execute SQL queries to analyze, profile, validate, and reconcile enterprise datasets.
• Investigate data discrepancies, inconsistencies, and quality issues across multiple systems.
• Use SQL joins, filters, and aggregations to understand relationships between datasets.
• Identify root causes of data issues and collaborate with technical teams to support resolution. Data Mapping & Lineage:
• Trace data from source systems through ETL/ELT pipelines, enterprise data warehouses, and reporting platforms.
• Analyze and document source-to-target mappings, data transformations, and dependencies.
• Understand how data is structured, modeled, transformed, and consumed across enterprise systems.
• Identify gaps in data definitions, mappings, and documentation. Data Governance & Quality:
• Support data governance initiatives focused on improving data accuracy, consistency, and reliability.
• Help establish and document business definitions, data quality standards, and authoritative data sources.
• Assist with data profiling, reconciliation, and validation activities.
• Support enterprise data management initiatives, including master and reference data where applicable. Business & Technical Collaboration:
• Partner with business users to understand how data is created, maintained, and utilized.
• Ask thoughtful questions to clarify business processes, data definitions, and reporting requirements.
• Collaborate with Data Engineering, BI, and other technical teams to investigate data-related issues.
• Document findings, requirements, data relationships, and recommendations clearly. REQUIRED QUALIFICATIONS:
• Ideally 4–6 years of experience in data analysis, data quality, data management, or a related discipline.
• Strong hands-on SQL skills, including writing queries, joining tables, filtering data, and investigating discrepancies.
• Solid understanding of relational database concepts, including primary keys, foreign keys, table relationships, and data structures.
• Experience with data mapping, data lineage, profiling, reconciliation, or data quality analysis.
• Understanding of how data moves through ETL/ELT pipelines and enterprise data warehouses.
• Experience working with complex enterprise datasets.
• Ability to independently investigate data issues, identify patterns, and determine root causes.
• Strong communication skills and experience collaborating with business users and technical teams.
• Excellent analytical thinking, attention to detail, documentation skills, and problem-solving abilities.

PREFERRED QUALIFICATIONS

• Experience with Snowflake or similar cloud data warehouse platforms.
• Experience with Power BI or Qlik Analytics.
• Familiarity with Master Data Management (MDM) and enterprise data governance concepts.
• Understanding of data modeling, dimensional modeling, data relationships, and data warehouse architecture.
• Experience working with ERP, customer, product, inventory, supply chain, or manufacturing data.
• Familiarity with metadata management, data catalogs, data stewardship, and data quality frameworks.
• Basic Python experience for data analysis or automation. IDEAL CANDIDATE PROFILE:
• The ideal candidate is a technically capable Data Analyst who enjoys researching complex data problems and understanding how information flows across enterprise systems.
• They are naturally curious, proactive, and comfortable working independently with large datasets while also collaborating directly with end users and technical stakeholders.
• Successful candidates should be able to explain not only how to query data using SQL, but also how to investigate where data originates, how it is transformed, and why discrepancies may occur between systems.
• This role is best suited for someone who enjoys hands-on data investigation rather than primarily developing dashboards, managing projects, or writing governance policies. INTERVIEW PROCESS: CANDIDATES SHOULD BE PREPARED TO DISCUSS:
• SQL querying, table joins, and practical data analysis.
• Relational database fundamentals, including primary and foreign keys.
• Experience investigating data discrepancies and tracing data lineage.
• Understanding of how data moves through enterprise systems and data warehouses. ·