Hello,
Hope this email finds you well.
This is Farhan from Arreglo Consulting.
I have a position matching your profile.
Please let me know your interest ASAP.
- Company: Kroger
- Title: Data Engineer
- Duration: 1 year+
- Interview: zoom video call with vendor, managerial ref check, phone/Skype with client and offer
Need 10+ years profile
Must Haves: Strong Databrick experience, ADF, enterprise experience
Job Description:
The client's team is looking for a Data Engineer experienced in implementing data solutions in Azure. The Data Engineer will analyze, design and develop enterprise data and information architecture deliverables, focusing on data as an asset for the enterprise. The Data Engineer will also support the implementation of Infrastructure as Code (IaC) by working with teams to help engineer scalable, reliable, and resilient software running in the cloud.
- Leverages enterprise standards for data domains and data solutions, focusing on simplified integration and streamlined operational and analytical uses
- Guides high level data architecture design (functional, non-functional) and ensures teams adhere to data architecture standards
- Develops information processes for data acquisition, data transformation, data migration, data verification, data modeling, and data mining
- Accountable for cost viability and technical estimation of data platform usage
- Designs data solutions for data distributions and partitions, scalability, disaster recovery and high availability
- Designs security for data policies and standards
- Monitors and optimizes data solutions
- Actively governs and automates standard data architecture patterns and blueprints
- Partners with architecture, security, infrastructure, and application teams to design and implement the automation of data, data platforms, and tools
- Creates and updates automation to eliminate routine management processes
- Articulates the need for scalability and understand the importance of improving quality through testing
- 5+ years of hands-on experience with data platforms
- Experience in designing data solutions in Azure including data distributions and partitions, scalability, disaster recovery and high availability
- Experience in monitoring and optimizing data solutions in Azure including using Azure Monitor
- Experience in implementing data solutions in Azure including Azure SQL, Azure Synapse, Cosmos DB, Databricks, ADLS, Blob Storage, ADF, Azure Stream Analytics
- Experience in designing security for data policies and standards
- In depth understanding and proficiency in automation of cloud platforms and data platforms
- Expertise in on-prem and cloud database automation and platform automation with Azure
- Proficiency with cloud automation tooling such as Ansible and Terraform
- Proficiency with DevOps and CI/CD methodologies and tools for automated infrastructure code test, integration, deployment, and assurance
- Proficiency with Languages such as Ruby, bash, Python or Go
- Experience with Software Development and automation methodologies
- Experience with data security best practices
- Strong problem-solving skills
- Strong collaboration skills and excellent verbal and written communication skills
Key Responsibilities
- Leverages enterprise standards for data domains and data solutions, focusing on simplified integration and streamlined operational and analytical uses
- Guides high level data architecture design (functional, non-functional) and ensures teams adhere to data architecture standards
- Develops information processes for data acquisition, data transformation, data migration, data verification, data modeling, and data mining
- Accountable for cost viability and technical estimation of data platform usage
- Designs data solutions for data distributions and partitions, scalability, disaster recovery and high availability
- Designs security for data policies and standards
- Monitors and optimizes data solutions
- Actively governs and automates standard data architecture patterns and blueprints
- Partners with architecture, security, infrastructure, and application teams to design and implement the automation of data, data platforms, and tools
- Creates and updates automation to eliminate routine management processes
- Articulates the need for scalability and understand the importance of improving quality through testing
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