JOB DESCRIPTION

Overview

The BICC team excels in data analytics, report development, and dashboard deployment, enabling us to deliver invaluable insights in the Health Life & Science organization at Microsoft.  Our team is dedicated to maximizing the potential of our products through data-driven decision-making.

We are looking for a Senior Software Engineer to join our team and help us build and maintain our cutting-edge Azure data engineering and analytics platform. This is an individual contributor role, so you will have the opportunity to work on challenging and impactful projects from start to finish.

We offer a challenging and rewarding work environment where you will have the opportunity to work on cutting-edge projects. We are a team of  experienced data engineers and analysts who are committed to developing the best possible solutions.

You would be responsible for Designing, developing, and maintaining data engineering and analytics solutions on Azure. Build and maintain data pipelines, data warehouses, and data lakes. Work with stakeholders to understand their data needs and develop solutions to meet those needs. Use Azure data services and frameworks to store, process, and analyze data. Develop and maintain data quality and governance procedures. Stay up to date on the latest Azure data engineering and analytics technologies.

Qualifications

Required Qualifications 

• Bachelor's, Master's, or PhD degree in Computer Science, Computer Engineering, Electrical Engineering or equivalent .
• 6+ yrs of exp as data engineer and 4+ yrs in Azure based solutions.
• 4 yrs of exp in ETL/ ELT, data modelling and datawarehousing
• 2+ Experience with securing data, products, tools, and processes.

Other Qualifications

Knowledge of data governance, security, and compliance practices.

Preferred Skills

• Microsoft Certification (related to Azure Data Engineer, Data Analyst or Data Scientist roles).
• Experience with modern application development techniques including: Microservices, RESTful APIs, and container-based deployment and orchestration (Docker, Kubernetes, etc.)
• Familiarity with programming languages such as Python, Scala, or Java for scripting and data manipulation.
• Technical, project or team leadership experience mentoring and guiding others.
• Experience with engineering interoperable solutions using common standards (such as hands-on experience with FHIR or DICOM) is a big plus.
• Experience with big data technologies and distributed computing frameworks.

Responsibilities:

• Design, develop, and deploy end-to-end data pipelines on the Azure platform, including data ingestion, transformation, and loading processes.
• Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and translate them into technical solutions.
• Implement data integration strategies to consolidate data from disparate sources into Azure-based repositories.
• Influence and create new designs, architectures, standards, and methods for large-scale distributed systems.
• Develop and maintain ETL processes using Azure Data Factory, Azure Databricks, or similar technologies.
• Create interactive and visually appealing data visualizations, dashboards, and reports using Power BI.
• Perform tasks related to securing services and infrastructure and incorporating a security centered mindset towards products, tools, and processes. 
• Collaborate closely with business users to gather reporting requirements and deliver actionable insights through Power BI.
• Monitor and optimize data pipelines for performance, reliability, data quality, and Power BI report performance.
• Ensure data security and compliance with relevant data regulations throughout the data lifecycle.
• Troubleshoot and resolve data pipeline and Power BI-related issues in a timely manner.
• Stay up-to-date with the latest Azure services, Power BI features, tools, and best practices in data engineering and visualization.
• Participate in code reviews, documentation, and knowledge sharing sessions with the team.
• Collaborate with infrastructure and DevOps teams to ensure the availability and scalability of data solutions.