Data and Analytics Architect
About The Position
The Data and Analytics Architect provides functional and technical leadership across data analysis and data management functions, including data modeling, SQL, data quality, data profiling, ETL, metadata enrichment and management, data provenance and lineage, and report design. The role works independently as a senior lead and may manage and direct analysis, design, and support activities for technical data management solutions across projects, including larger projects. The position is based in Charlotte, North Carolina, with three days onsite per week. The role requires experience supporting data analytics, data warehouse, or data integration work in an agile environment, as well as hands-on work with Databricks data engineering and related data platforms and tools.
Requirements
- 8–10 years of experience.
- Experience as a business systems analyst (BSA) in data analytics, data warehouse, or data integration in an agile environment.
- Strong experience in data analysis, profiling, cleanup, data wrangling, and validation.
- Hands-on experience building data quality checks and writing complex SQL queries.
- Experience with Jira, Confluence, and Bitbucket.
- Demonstrable experience with conceptual, logical, and physical data modeling techniques.
- Strong analytical, organizational, and technical skills to analyze, model, and interpret data.
- Good understanding of data security classifications and Risk Assessment (TRMIS) guidelines.
- Experience supporting legacy applications, including mainframe and other on-premises applications, and migrating legacy solutions using COTS products.
- Experience conducting current-state analysis through reverse engineering and identifying source and downstream systems.
- Experience conducting feasibility analysis, project scoping, and project work estimation.
- Experience developing requirements through elicitation, analysis, specification, and validation.
- Hands-on experience capturing data lineage and data mapping between source and target systems.
- Good knowledge of Source to Target Mapping (STTM) documentation.
- Good communication skills.
- Mandatory skill: Databricks data engineering.
Nice To Haves
- Experience with at least two of the following in addition to Databricks: Azure Data Factory, Python/PySpark, Tableau, Power BI, mainframe, or SAS.
Responsibilities
- Provide functional and technical leadership across data analysis and data management functions.
- Perform data modeling, SQL, data quality, data profiling, ETL, metadata enrichment and management, data provenance and lineage, and report design work.
- Independently lead and potentially manage or direct the analysis, design, and support of technical data management solutions across projects.
- Analyze, profile, clean, wrangle, and validate data; build data quality checks and write complex SQL queries.
- Conduct current-state analysis through reverse engineering and identify source and downstream systems.
- Conduct feasibility analysis, scope projects, and provide project work estimates.
- Develop requirements through elicitation, analysis, specification, and validation.
- Capture data lineage and data mappings between source and target systems.
- Support legacy applications, including mainframe and other on-premises applications, and migration of legacy solutions using COTS products.
- Work with Source to Target Mapping (STTM) documentation.
Benefits
- Medical and dental benefits options
- Disability insurance
- Paid time off, inclusive of sick leave
- Other paid and unpaid leave options
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
