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Azure Data Engineer - Richmond, United States - Cognizant Technology Solutions
Description
We are Cognizant Artificial Intelligence
Digital technologies, including analytics and AI, give companies a once-in-a-generation opportunity to perform orders of magnitude better than ever before. But clients need new business models built from analyzing customers and business operations at every angle to really understand them.
With the power to apply artificial intelligence and data science to business decisions via enterprise data management solutions, we help leading companies prototype, refine, validate and scale the most desirable products and delivery models to enterprise scale within weeks
*You must be legally authorized to work in United States without the need of employer sponsorship, now or at any time in the future *
This is a remote position open to any qualified applicant in the United States
Job Title: Azure Data Engineer
Role/Responsibilities
· Work collaboratively and creatively with other data engineers to develop scalable and maintainable data pipelines using the latest Microsoft Azure technologies and leading industry practices
· Develop patterns and build data pipelines that ingest enterprise-wide data into the Enterprise Data Lake and make it available for consummation for both data analytics and data science
· Optimize and productionize Data pipelines
· Partner with a variety of internal stakeholders across the organization to deliver creative, cutting-edge, high-quality engineering solutions that meet business requirements in a fast-paced, ever-changing business environment
Required Experience/Qualifications
• 3-5 Years of Experience in Data Engineering including guiding ideation, design, and decisions in a collaborative team setting
• 1-2 years experience with cloud computing, on Microsoft Azure
• Experience developing scalable and supportable Enterprise Data Lake patterns
• 1-2 years experience in Data pipeline development using Azure Data Factory, Azure Databricks and Delta Lake
• 1-2 years experience working with Big Data frameworks, preferably Apache Spark
• 1-2 years of development experience in either Pyspark, Python, C#, Scala, or Java
• 1-2 years experience working with transactional/relational data and SQL
• Experience working on Agile teams implementing DevOps practices
• Excellent communication skills, adapting to various audience types
• Strong on ideas for system optimization, support, Data Reconciliation, Testing and monitoring
• Passionate about innovation and loves solving complex problems in a highly- collaborative, fast-paced team environment
Preferred Qualifications:
• Good to have Snowflake knowledge
• Focus on complete solutions including unit/function/integration testing, documentation, pipeline monitor
• Prior Experience migrating data pipelines from On-prem to Cloud
• Linux Shell scripting
• Stored procedures
• Azure Monitoring tools (Log Analytics, Azure functions, Logic Apps, Kusto
• Data Security (Encryption)
Soft skills
· Good communication & interpersonal skills
· Great attitude
· Problem solving
· Collaboration – Should work collaboratively with Global team (offshore and EU team members)
Salary and Other Compensation:
Applications will be accepted until 05/04/2024.
The annual salary for this position is between $80,000 – $100,000 depending on experience and other qualifications of the successful candidate.
This position is also eligible for Cognizant's discretionary annual incentive program, based on performance and subject to the terms of Cognizant's applicable plans.
Benefits: Cognizant offers the following benefits for this position, subject to applicable eligibility requirements:
· Medical/Dental/Vision/Life Insurance
· Paid holidays plus Paid Time Off
· 401(k) plan and contributions
· Long-term/Short-term Disability
· Paid Parental Leave
· Employee Stock Purchase Plan
·
Disclaimer: The salary, other compensation, and benefits information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law.
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