Job Description

Role Summary:

The role of the Data Analyst is to engage business stakeholders and be part of project teams to understand, verify and document business requirements with a core focus on data needs, including but not limited to how data are linked to business strategy, architected/modeled, created/secured, required for operational and analytical usage, shared, measured for data quality, protected/secured, and retained. The output from these analyses are data plans, that are the basis for utilizing existing data capabilities and evolving new data capabilities to deliver solutions and meet business needs. The role requires strong central problem analysis and solving skills, and effective communication skills to translate business data requirements to Data Architects/Modelers, Engineers/Wranglers, Data Owners/Stewards, BI Solution Developers, and other business and technical roles.  The role could potentially provide involve one or more of the following focus areas: Data Governance, Logical Data Modeling, Master Data Management, Data Quality Management, and Data Protection.

Key Responsibilities:

Engage business leaders/staff and technology leaders/staff in an end-to-end process to understand and communicate data requirements and translate to develop solutions
Apply problem-solving techniques to find impact, root cause analysis, and solution options
Essay solutions to verify traceability to requirements
Data Governance: Understand key business and technical decisions through-out the lifecycle of data. Own the evolution and champion adoption of key data governance capabilities including data cataloging, metadata management, lineage, data quality and master data management. Engage and support Data Owners and Data Stewards.
Logical Data Modeling: Understand data requirements and translate to conceptual and Logical Data Models (LDM). Model data attributes, data rules, and relationships. Facilitate development and consensus on data standards and rules. Translate LDM constructs to publish in data catalogs, and to Data Architects/Modelers, Data Engineers, BI Developers and Data Scientists.
Master Data Management: Assess needs to develop a “golden source” of high-quality master data. Develop data cleansing, match/merge and survivorship rules, and operational metrics.  Gain insights from metrics to evolve MDM/RDM capabilities.

Data Quality: Use automated tools to profile data sources to measure current state data quality. Develop data quality rules and metrics. Track and assess data defects and find root-causes.
Data Protection: Assess select data sources (databases, file shares, etc.) using automated scanning technologies, assess and identify potential gaps in data security with a focus on highly sensitive data (e.g., Personal Identifying Information).

Qualifications:

5+ years of relevant experience performing data analysis

Experience in…

Solving problems of various low to high complexity
Developing insights from the analysis of data
Use of process and data modeling techniques and tools to represent current state and future state design and concept of operations
Leading/driving common business glossary/terminology, definitions and business rules
Using and supporting various data management tools and technologies including but not limited to data cataloging, data quality/profiling, and data lineage
Data warehousing, business intelligence/reporting, analytics and/or data science
Master Data Management projects and capabilities is highly desirable
Making and delivering presentations to business and technical staff
Supporting change and managing transitions is highly desirable
The Insurance industry is highly desirable

Required Skills/Knowledge:

Ability to understand and assess data needs in a business, process and analytical context
Ability to understand, represent and translate business data requirements - verbally and in written form - to a variety of business and technical roles
Strong problem analysis and solving
Strong ability to model current and future state business processes and data domains/entities
Ability to discover and understand data, data models, data rules and causal relationships at a summary and detailed level
Strong technical proficiency and demonstrated ability with data management technologies such as data quality profiling tools, data catalog, and master data management
Ability to perform basic project management functions such as project plan development and resource / time estimation of tasks
Ability to essay solutions to find traceability to requirements
Demonstrated ability to collaborate, communicate, build relationships, mentor and influence a community of data professionals across lines of business and functional areas

Education:

Required:

Bachelor’s degree; equivalent work experience accepted

Preferred:

M.B.A. or Master’s in Management or Technology; equivalent work experience accepted