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Job description
Collaborates with analytics and business teams to improve data models that feed business intelligence tools, increase data accessibility, and fostering data-driven decision making across the organization.
Implement processes and systems to monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it
Writes unit/integration tests, contributes to engineering wiki, and documents work.
Designs and develops data integrations and data quality framework
Bachelor of Engineering or equivalent degree in Computer Science or a related technical field
At least 7+ years of experience in the Data engineering field.
6+ years of experience in Big Data, Hadoop Ecosystem, Spark, Python, SQL, Hive,
Proficiency in relational SQL and NoSQL databases.
In-depth skills in developing and maintaining ETL/ELT data pipelines
Experience in data modelling techniques such as Kimball star schema.
Hands-on experience with Azure Cloud services such as Azure Data Factory (ADF), Databricks, and Cloud Storage.
Proficient In Airflow configuration and creating dependencies .
Experience in workflow management tools such as Airflow, Data streaming App such as Kafka, and CI/CD tools
Excellent communication and collaboration skills, with the ability to work effectively in a team environment
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Qualification
Develops and maintains scalable data pipelines to support continuing increases in data volume and complexity.
Collaborates with analytics and business teams to improve data models that feed business intelligence tools, increase data accessibility, and fostering data-driven decision making across the organization.
Implement processes and systems to monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it
Writes unit/integration tests, contributes to engineering wiki, and documents work.
Designs and develops data integrations and data quality framework
Bachelor of Engineering or equivalent degree in Computer Science or a related technical field
At least 7+ years of experience in the Data engineering field.
6+ years of experience in Big Data, Hadoop Ecosystem, Spark, Python, SQL, Hive,
Proficiency in relational SQL and NoSQL databases.
In-depth skills in developing and maintaining ETL/ELT data pipelines
Experience in data modelling techniques such as Kimball star schema.
Hands-on experience with Azure Cloud services such as Azure Data Factory (ADF), Databricks, and Cloud Storage.
Proficient In Airflow configuration and creating dependencies .
Experience in workflow management tools such as Airflow, Data streaming App such as Kafka, and CI/CD tools
Excellent communication and collaboration skills, with the ability to work effectively in a team environment
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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