Data Engineer (remote)

• Data Architecture, Ontology Taxonomy Design
• Design and implement scalable data architectures to support advanced analytics, reporting, and business needs.
• Develop and maintain ontologies, taxonomies, and metadata frameworks to standardize and govern data assets.
• Collaborate with business stakeholders to ensure data consistency, accuracy, and accessibility.
• Implement and maintain Master Data Management (MDM) platforms to centralize and standardize key business data.
• ETL Development Data Integration
• Develop and optimize ETL pipelines using Azure Data Factory (ADF) and SSIS to ingest, clean, and transform data.
• Integrate and manage data from diverse sources into data lakes or data warehouses for analytics and platform offering.
• Automate and monitor data workflows, ensuring data quality, performance, and reliability.
• Collaborate on integrating AI/ML workflows into ETL pipelines to enable advanced analytics capabilities.
• Data Warehousing
• Design, develop, and optimize enterprise-level data warehouses using Azure Synapse Analytics and SQL Server .
• Implement efficient data models (e.g., star schema, snowflake schema) to support business intelligence and analytics.
• Ensure scalability, performance, and accessibility of warehousing solutions to meet business needs.

Power BI Data Visualization

• Collaborate with business teams to develop Power BI dashboards and reports.
• Enable advanced reporting capabilities by integrating semantic models, ontologies , and centralized data into Power BI.
• Ensure visualizations provide meaningful insights to both technical and non-technical stakeholders.

AI/ML Integration

• Assist in preparing and transforming data for AI/ML models to enable predictive and prescriptive analytics.
• Build data pipelines to support model training, feature engineering, and deployment of AI solutions.
• Work with AI teams (or tools) to integrate insights into the business reporting and data workflows.

Collaboration and Best Practices

• Work closely with analysts and engineers to align data engineering outputs with enterprise data goals.
• Implement and promote best practices for data governance, quality, and security .
• Mentor junior team members and drive a culture of innovation, collaboration, and learning.

Qualifications:

Education

• Bachelor s or Master s degree in Computer Science, Data Engineering, or a related field.

Experience

• 5+ years of experience as a Data Engineer with a strong focus on the Microsoft technology stack .
• Proven experience with data architecture , ontology, taxonomy design, and metadata management.
• Hands-on experience building ETL pipelines using Azure Data Factory (ADF) and SSIS .
• Strong experience designing and maintaining data warehouses (Azure Synapse Analytics, SQL Server).
• Experience with Master Data Management (MDM) platforms to support data consistency and governance.
• Exposure to AI/ML concepts and their integration into ETL pipelines or reporting workflows.

Technical Skills

• Strong proficiency in SQL and data modeling (star schema, snowflake schema).
• Hands-on experience with Azure services: Azure Data Factory, Azure Synapse Analytics, Azure SQL Database, Azure Data Lake .
• Proficiency in Power BI for building dynamic and insightful dashboards.
• Knowledge of Python or other scripting languages for automation and integration.
• Understanding of big data solutions (e.g., Azure Data Lake) and modern data processing pipelines.
• Familiarity with AI/ML data preparation and model deployment.

Soft Skills

• Strong analytical and problem-solving mindset.
• Excellent communication and collaboration skills, with the ability to work cross-functionally with business stakeholders.
• Ability to translate complex technical solutions into business-friendly language.