Senior data specialist responsible for leading data mapping, documenting field-level mappings and lineage, ensuring data quality and validation, performing reconciliation, collaborating with engineers and stakeholders, and building reports/dashboards to support analytics and governance across Azure/Databricks enterprise data platforms.
Job Title: Data Analytical Specialist/Scientist - Senior
Location: Hybrid – 3 days onsite / 2 days remote (subject to change)
Contract: 6 month contract
Pay Rate: $70 - $75/hr depending on experience.
About the Role
Our client is looking for an experienced Data Analytical Specialist/Scientist to join a high-performing Data Platform team. This team is responsible for delivering scalable, secure, and reliable data and cloud infrastructure solutions across the enterprise.
You will play a key role in ensuring data accuracy, integrity, and alignment across complex data ecosystems, working with modern technologies including Azure, Databricks, and enterprise data platforms.
Must-Have Requirements
- 8+ years of experience in Data Mapping & Documentation
- 8+ years of experience in Data Quality & Validation
- 8+ years of hands-on experience with Microsoft Azure
Key Responsibilities
Data Mapping & Documentation
- Lead detailed data mapping across source systems, data platforms, and target environments
- Document field-level mappings, transformation logic, data lineage, and business rules
- Ensure alignment with enterprise data standards, governance, and architecture
- Maintain clear, version-controlled mapping documentation for engineering teams
- Analyze and profile datasets to identify structures, relationships, and data quality issues
- Identify data gaps, inconsistencies, and risks during migration or integration
Stakeholder Collaboration
- Collaborate with data engineers, architects, business analysts, and product owners
- Translate business requirements into technical mapping documentation
- Facilitate workshops to resolve data ambiguities and define business rules
Data Quality & Validation
- Define validation rules and expected outputs for testing teams
- Perform data reconciliation between source and target systems
- Partner with data governance teams to improve data quality and metadata accuracy
Reporting & Insights
- Develop dashboards and reports (e.g., Power BI) to support business needs
- Present insights and recommendations to both technical and non-technical stakeholders
- Contribute to self-service analytics and reporting frameworks
Note: AI-enabled tools may be used to sort applications based on job-related criteria. All AI generated results are vetted by our team and the decision of which candidates move forward is always made by a human.
BEV123
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