Job Summary:

We are looking for a highly skilled and experienced Senior Data Architectwith a comprehensive background in data engineering, data science, and analytics. The ideal candidate will be adept at building and optimizing data pipelines, analyzing large datasets, and applying advanced analytics to drive business insights. With strong expertise in data management, modeling, and visualization, this role supports data-driven decision-making across diverse domains, such as healthcare, finance, and business intelligence.

Key Responsibilities:

• Design, implement, and maintain scalable data pipelines and workflows to process large volumes of structured and unstructured data.
• Analyze and interpret complex datasets to extract meaningful insights that support strategic business initiatives.
• Develop and optimize data models, dashboards, and visualizations for effective decision-making.
• Build machine learning models and predictive analytics solutions to address business challenges.
• Collaborate with stakeholders to gather requirements and translate them into data solutions.
• Ensure data quality, security, and compliance with organizational and industry standards.
• Manage data migration, integration, and transformation processes across platforms.
• Support production environments by troubleshooting issues and optimizing system performance.
• Stay updated with emerging trends and technologies in data engineering, analytics, and machine learning.

Qualifications:

• Proven experience in data engineering, data science, and analytics.
• Strong understanding of data processing, storage, and retrieval techniques.
• Expertise in statistical analysis, machine learning, and data visualization methods.
• Proficiency in programming and scripting languages for data analysis and engineering tasks.
• Familiarity with data governance, security, and compliance frameworks.
• Excellent analytical thinking, problem-solving, and communication skills.

Preferred Skills:

• Experience with big data ecosystems and cloud-based data platforms.
• Knowledge of data testing frameworks and job scheduling tools.
• Strong domain expertise in industries like healthcare, finance, or marketing.
• Leadership and collaboration skills for cross-functional teamwork.

Education and Experience:

• Bachelor's degree in Computer Science, Data Science, or a related field. Master's degree is a plus.
• 7+ years of professional experience across data engineering, data science, and analytics roles.