Job Description

Position Overview

The Senior Data Architect & AI Solutions Engineer will lead the design, development, and deployment of a modern data warehouse and analytics platform. This role is responsible for transforming raw data into actionable insights and predictive models to support strategic business decisions. The ideal candidate will have extensive experience in data architecture, data warehousing, and AI model implementation in a cloud-based environment.

Key Responsibilities

Data Warehouse Architecture & Design

• Design and implement scalable, high-performance data warehousing solutions using Microsoft Azure technologies (e.g., Azure Synapse Analytics, Azure Data Lake, SQL Server).
• Build and manage ETL/ELT pipelines to ingest and integrate data from multiple sources.
• Develop data storage, retrieval, and archiving strategies for large-scale datasets.

Analytics & Reporting

• Translate business needs into data and reporting solutions that support decision-making.
• Develop interactive dashboards and reports using Power BI and similar tools.
• Conduct advanced data analysis to uncover trends and inform strategic planning.

AI & Predictive Modeling

• Design and deploy machine learning models to enable predictive analytics and forecasting.
• Utilize tools such as Azure Machine Learning and Databricks to operationalize models.
• Identify business challenges that can be addressed through AI and predictive modeling.

Data Science Collaboration

• Serve as a liaison between data teams and business stakeholders to ensure alignment.
• Support the development of data pipelines for machine learning model training and scoring.
• Implement automation to optimize workflows in data science and model deployment.

Project Leadership & Mentorship

• Lead the full lifecycle of data infrastructure projects, from planning through production deployment.
• Provide mentorship to junior data engineers and data scientists.
• Manage the integration of legacy systems into modern data architectures.

Qualifications

Education & Experience

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related discipline.
• At least 8 years of experience in data architecture, warehousing, and analytics in large-scale environments.
• Extensive experience with Microsoft Azure Data Services (e.g., Synapse, SQL Database, Data Lake).
• Demonstrated success in developing and maintaining AI/machine learning models.

Technical Skills

• Proficiency in SQL and data modeling techniques.
• Experience with ETL tools such as Azure Data Factory and SSIS.
• Skilled in BI/reporting platforms including Power BI, Tableau, or similar.
• Strong understanding of machine learning algorithms, statistical models, and tools such as Python, R, Azure ML, and Databricks.
• Familiarity with version control (Git), DevOps practices, and CI/CD pipelines.

Preferred Qualifications

• Microsoft Azure certifications (e.g., Azure Data Engineer Associate, Azure AI Engineer Associate).
• Experience with advanced analytics techniques, including deep learning, NLP, and time-series forecasting.
• Familiarity with big data technologies such as Hadoop and Spark, especially within Azure-based ecosystems.

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