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Job description
Kforce has a client that is seeking a Data Analyst in Tempe, AZ.
Key Responsibilities:
* Perform detailed data analysis on source system data to identify anomalies, inconsistencies, and data quality issues
* Support data analysis, profiling, and transformation activities across legacy and target systems, including movement between relational, NoSQL, and object storage environments
* Develop and maintain two-way data mappings (source-to-target and target-to-source) to ensure completeness, traceability, and alignment with business requirements
* Maintain a strong understanding of target data models, database structures, and data usage patterns to support accurate transformation and validation
* Contribute to the architecture and management of data lake and data warehouse solutions, ensuring data is structured, performant, and accessible for downstream consumption
* Collaborate with Business Analysts, Technical Architects, and development teams to translate business rules into data mappings and transformation logic
* Identify data quality issues, anomalies, and gaps; support data cleansing decisions; And ensure alignment with approved data mapping and transformation rules
* Perform and support data validation and reconciliation activities to confirm data accuracy, completeness, and usability across all pipeline and migration processes
* Document data flows, schemas, mappings, and transformation logic to support traceability, auditability, and governance requirements
* Contribute to the continuous improvement of data platform architecture, tooling, and data migration strategies in alignment with organizational standards and best practices
REQUIREMENTS:
* 3+ years of experience in data analysis, development, or a related role supporting data integration or migration initiatives
* Solid understanding of database design principles, including relational modeling, normalization, and denormalization strategies
* Demonstrated ability to move and transform data across structured, semi-structured, and unstructured formats
* Experience supporting data mapping, transformation, and validation activities within data migration or integration contexts
* Proficiency in SQL, including experience with Azure SQL Database, Azure SQL Managed Instance, or similar relational platforms
Nice to Have:
* Experience with MS SQL Server, Azure Cosmos DB or other NoSQL database platforms supporting distributed or semi-structured data models
* Knowledge of Kusto Query Language (KQL) and experience with Azure Monitor and/or Azure Data Explorer for data analysis, logging, and performance insights
* Experience designing and working with object storage patterns, including blob- and file-based data architectures
* Exposure to data science or advanced analytics concepts, including familiarity with platforms such as Azure Machine Learning, Microsoft Fabric/Foundry, Databricks, or similar tools
* Understanding of data governance practices, including data lineage, cataloging, and metadata management to support traceability and auditability of data assets
* Experience working with data lakes and/or data warehouse platforms (e.g., Azure Data Lake Storage, Microsoft Fabric, or similar technologies)
What We're Looking For:
You think critically about how data flows across systems and understand the importance of data quality, integrity, and traceability in complex environments. You are energized by solving data transformation and integration challenges and can navigate ambiguity while maintaining a structured, analytical approach to problem-solving.
The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future.
We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability & ADD insurance to eligible employees. Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off unless required by law. Hourly employees on a Service Contract Act project are eligible for paid sick leave.
Note: Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce's sole discretion unless and until paid and may be modified in its discretion consistent with the law.
This job is not eligible for bonuses, incentives or commissions.
Kforce is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.
By clicking ?Apply Today? you agree to receive calls, AI-generated calls, text messages or emails from Kforce and its affiliates, and service providers. Note that if you choose to communicate with Kforce via text messaging the frequency may vary, and message and data rates may apply. Carriers are not liable for delayed or undelivered messages. You will always have the right to cease communicating via text by using key words such as STOP.
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Frequently asked questions
Q: What skills or qualities help someone succeed as a Data Analyst?
A: To succeed as a Data Analyst, key technical skills include proficiency in programming languages such as Python or R, expertise in data visualization tools like Tableau or Power BI, and knowledge of statistical analysis and machine learning concepts. Additionally, strong soft skills like effective communication, problem-solving, and collaboration are crucial for presenting insights to stakeholders and working with cross-functional teams. By combining these technical and soft skills, Data Analysts can drive business decisions, identify areas for improvement, and contribute to the growth and success of their organization.
Q: What is the career path for a Data Analyst?
A: A Data Analyst's typical career progression involves starting as an Entry-Level Data Analyst, where they collect, analyze, and interpret data to inform business decisions. As they gain experience, they can move into Mid-Level roles such as Senior Data Analyst or Business Analyst, where they take on more complex projects and lead smaller teams. Ultimately, they can advance to Senior Leadership positions like Data Scientist, Data Manager, or even Director of Analytics, where they oversee large-scale data initiatives and drive strategic business growth.\n\nKey opportunities for skill development and professional growth in this role include learning programming languages like Python or R, mastering data visualization tools like Tableau or Power BI, and staying up-to-date with emerging trends in machine learning and artificial intelligence. Additionally, Data Analysts can develop soft skills like communication, project management, and leadership to excel in their roles.\n\nLong-term career prospects for Data Analysts are diverse, with potential directions including transitioning into related fields like Business Intelligence, Data Engineering, or even becoming a Product Manager, or pursuing advanced degrees in Data Science or related fields to further specialize in areas like machine learning or data engineering.
