Azure Data Architect

Job Title

Location: 100% Remote. This is a United States based position, and candidates must reside in the continental United States to be eligible for employment.

Years' Experience: 10+ Years of professional experience.

Education: Bachelor's degree in computer science, Data Science, Statistics, or related field.

Clearance: Applicants must be able to obtain and maintain a secret security clearance. United States Citizenship is required as part of the eligibility criteria to be able to obtain this type of security clearance.

Certifications:

• Active CompTIA Security+ Certification

Key Skills:

• Expertise in statistical modeling, machine learning algorithms, and data mining techniques.
• Must have strong expertise in the Azure Cloud environment
• Strong proficiency in Python or similar language and SQL for data preparation, analysis, and modeling

Responsibilities

• Data Science Strategy: Develop and implement a data science strategy for the project, aligning with strategic goals and objectives.
• Problem Identification: Work with stakeholders to identify opportunities to leverage data to improve HR processes, such as recruitment, retention, training, and performance management.
• Data Exploration & Analysis: Lead the exploration and analysis of large datasets to identify trends, patterns, and insights to understand data quality, gaps, and potential enhancements.
• Model Development: Design, develop, and validate predictive models using machine learning algorithms and statistical techniques.
• Model Deployment: Deploy and maintain machine learning models in a production environment, ensuring scalability and reliability.
• Data Visualization: Create compelling data visualizations using tools such as Power BI to communicate insights to stakeholders.
• Team Leadership: Lead and mentor a team of data scientists, providing technical guidance and support.
• Collaboration: Collaborate with other teams, including software developers, system architects, and business analysts, and to integrate data science solutions.
• Data Quality: Ensure data quality and accuracy by implementing data validation and cleansing processes.
• Compliance: Ensure that all data science activities comply with relevant and DoD regulations and security policies.
• Research & Development: Stay up to date with the latest advances in data science and machine learning and explore new technologies and techniques to improve HR processes.
• Documentation: Create and maintain detailed documentation of data science processes, models, and results.

Qualifications

• 10+ years of experience in data science, machine learning, and statistical modeling.
• Bachelor's degree in data science, Statistics, Mathematics, Computer Science, or a related quantitative field experience
• Active Secret security clearance
• Active CompTIA Security+ certification
• Expertise in statistical modeling, machine learning algorithms, and data mining techniques.
• Experience with cloud computing platforms (e.g., Azure, Data Lake, Synapse Analytics, Machine Learning, Databricks, Logic Apps, AI Foundry).
• Proficiency in programming languages such as Python, R, SQL, PySpark
• Strong proficiency in Python or similar language and SQL for data preparation, analysis, and modeling
• Experience with data visualization tools (e.g., Power BI).
• Hands on experience with Microsoft Dataverse for data storage and management.
• Strong experience with data extraction, cleaning, and transformation (ETL) processes.
• Experience in data governance, metadata management, and data cataloging.
• Strong understanding of database technologies and SQL.
• Experience with Microsoft Power Platform (Power BI, Power Automate) is a plus.
• Excellent communication, presentation, and leadership skills.

About Sparibis

Sparibis LLC is a professional solution firm that Clients rely on to access the best talent to drive their business success.

Sparibis is an equal opportunity employer that values diversity at all levels. All individuals, regardless of personal characteristics, are encouraged to apply.