Degree in Data Analytics/Computer Science or equivalent work experience
3 years plus experience as an Azure Data Engineer or in a similar data engineering role using Microsoft Azure Cloud (Data Factory, Azure Functions, Databricks, etc.).
Practical Experience to Azure Fabric (Ideally DP-700 certified)
Proven experience in building and optimising big data pipelines and architectures
Strong analytical skills, especially in working with unstructured data
Proficient in designing and implementing well-written code
Experience with data pipeline testing, from source to presentation layer including troubleshooting skills
Key Responsibilities
Design, implement, and maintain data pipelines for data ingestion, processing, and transformation in Azure.
Work together with data scientists and analysts to understand the needs for data and create effective data workflows.
Create and maintain data storage solutions including Azure SQL Database, Azure Data Lake, and Azure Blob Storage.
Utilizing Azure Data Factory or comparable technologies, create and maintain ETL (Extract, Transform, Load) operations.
Implementing data validation and cleansing procedures will ensure the quality, integrity, and dependability of the data.
Improve the scalability, efficiency, and cost-effectiveness of data pipelines.
Monitoring and resolving data pipeline problems will guarantee consistency and availability of the data.
Skills and Experience:
Degree in Data Analytics/Computer Science or equivalent work experience
3 years plus experience as an Azure Data Engineer or in a similar data engineering role using Microsoft Azure Cloud (Data Factory, Azure Functions, Databricks, etc.).
Practical Experience to Azure Fabric (Ideally DP-700 certified)
Proven experience in building and optimising big data pipelines and architectures
Strong analytical skills, especially in working with unstructured data
Proficient in designing and implementing well-written code
Experience with data pipeline testing, from source to presentation layer including troubleshooting skills
Key Responsibilities
Design, implement, and maintain data pipelines for data ingestion, processing, and transformation in Azure.
Work together with data scientists and analysts to understand the needs for data and create effective data workflows.
Create and maintain data storage solutions including Azure SQL Database, Azure Data Lake, and Azure Blob Storage.
Utilizing Azure Data Factory or comparable technologies, create and maintain ETL (Extract, Transform, Load) operations.
Implementing data validation and cleansing procedures will ensure the quality, integrity, and dependability of the data.
Improve the scalability, efficiency, and cost-effectiveness of data pipelines.
Monitoring and resolving data pipeline problems will guarantee consistency and availability of the data.
Key job details
About Virtusa
Teamwork, quality of life, professional and personal development: values that Virtusa is proud to embody. When you join us, you join a team of 27,000 people globally that cares about your growth — one that seeks to provide you with exciting projects, opportunities and work with state of the art technologies throughout your career with us.
Great minds, great potential: it all comes together at Virtusa. We value collaboration and the team environment of our company, and seek to provide great minds with a dynamic place to nurture new ideas and foster excellence.
Virtusa is an Equal Opportunity Employer. All applicants will receive fair and impartial treatment without regard to race, color, religion, sex, national origin, ancestry, age, legally protected physical or mental disability, protected veteran status, status in the U.S. uniformed services, sexual orientation, gender identity or expression, marital status, genetic information or on any other basis which is protected under applicable federal, state or local law.
Applicants may be required to attend interviews in person or by video conference. In addition, candidates may be required to present their current state or government-issued ID during each interview. All candidates must be authorized to work in the USA.
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