Cleared Data Analyst (5553)

Summary

SMX is a technical and domain expertise company focused on enabling secure mission acceleration through digital transformation solutions. The Data Analyst will profile data sources, document data lineage, align data to canonical models, and support enterprise data products, APIs, and analytics. The role also involves developing data rules, producing technical documentation, and communicating requirements with engineering teams, clients, and stakeholders.

Responsibilities

• Profile data sources to assess structure, quality, completeness, and relationships, and document findings that inform mapping and design decisions
• Document end-to-end data lineage — tracing how data moves across systems through its full lifecycle, from origin through transformation to consumption
• Align source data to a canonical/domain data model, mapping source elements to target structures to support database design and consistent enterprise definitions
• Apply data elements to API schema design, translating business and data requirements into schemas that build teams can implement
• Develop and document data rules — standardization, validation, and quality rules — and apply Master Data Management (MDM) and well-managed data practices
• Produce clear technical documentation (source-to-target mappings, data dictionaries, metadata, and lineage artifacts) that other teams can build from
• Communicate technical requirements to engineering and build teams, and gather and clarify data requirements directly with clients and stakeholders
• Collaborate with data engineers, architects, and analysts to ensure mapped data meets downstream needs for products, APIs, and analytics

Skills

• Bachelor's degree in Computer Science, Information Technology, Data Engineering, Information Systems, or a related field
• 2–6 years of professional experience in data analysis, data mapping, data modeling, or a related data role
• Strong SQL skills and the ability to profile, query, and analyze data across multiple source systems
• Experience with data mapping and source-to-target documentation
• Working knowledge of data modeling and domain/canonical data models, schema design, and database design concepts
• Understanding of the end-to-end data lifecycle and how data moves across integrated systems
• Familiarity with API schema design and how data elements map to API contracts
• Strong technical writing skills and the ability to communicate requirements to both technical and non-technical audiences
• Experience with Master Data Management (MDM), golden-record concepts, and survivorship rules
• Experience with data governance, metadata management, data quality frameworks, and lineage tooling
• Experience defining data rules and validation logic for ingestion or transformation processes
• Familiarity with cloud data platforms (e.g., Databricks, Snowflake, AWS) and modern data catalogs
• Exposure to data-as-a-product or domain-driven data design
• Experience working in Agile delivery teams and communicating requirements to build/engineering teams

Qualifications

Must Haves

• Bachelor's degree in Computer Science, Information Technology, Data Engineering, Information Systems, or a related field
• 2–6 years of professional experience in data analysis, data mapping, data modeling, or a related data role
• Strong SQL skills and the ability to profile, query, and analyze data across multiple source systems
• Experience with data mapping and source-to-target documentation
• Working knowledge of data modeling and domain/canonical data models, schema design, and database design concepts
• Understanding of the end-to-end data lifecycle and how data moves across integrated systems
• Familiarity with API schema design and how data elements map to API contracts
• Strong technical writing skills and the ability to communicate requirements to both technical and non-technical audiences

Nice to Haves

• Experience with Master Data Management (MDM), golden-record concepts, and survivorship rules
• Experience with data governance, metadata management, data quality frameworks, and lineage tooling
• Experience defining data rules and validation logic for ingestion or transformation processes
• Familiarity with cloud data platforms (e.g., Databricks, Snowflake, AWS) and modern data catalogs
• Exposure to data-as-a-product or domain-driven data design
• Experience working in Agile delivery teams and communicating requirements to build/engineering teams

Benefits

• Health insurance
• Paid leave
• Retirement
• Learning & development opportunities