Description:
As the Sr Azure Data Engineer, you will focus on the continuous delivery of cloud-based ETL/ELT data processes and implementations. The ideal candidate will have the necessary technology and communication skills to manage hands-on highly visible and complex projects from start to finish. This role requires proficiency with developing realistic project plans to meet delivery objectives and the ability to maintain and establish required service levels. You will be a part of a fast-paced, entrepreneurial environment, which thrives on delivering transformational solutions and maximizing value to their stakeholders. As a participant of the cloud transformation process, you must be passionate about data, be a change agent and mentor, and a strong collaborator with the various business and technology stake holders. Hybrid Role – 3 days in office (T-TH)
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Data sourcing and source system analysis.
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Implement and build data pipelines for a data warehouse using Azure Data Engineering Stack – Adeptia (Third Party ETL/ELT tool), Azure Data Factory, Azure Synapse and ADLS.
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Combine technical expertise and problem-solving passion to work closely with clients, turning complex ideas into end-to-end solutions that transform our business offerings.
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Lead, design, develop and deliver large-scale data systems, data processing and data transformation projects that deliver business value for clients.
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Conduct technical feasibility assessments and provide project estimates for the design and development of the solution.
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Provide technical inputs to agile processes, such as user story, and task definition to resolve issues and remove barriers throughout the lifecycle of client engagements.
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Automate data platform operations and manage the post-production system and processes.
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Mentor, help and grow junior team members.
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Test, plan, creation and test programming using automated testing frameworks, data validation and quality frameworks, and data lineage frameworks.
EEO
Requirements:
- Bachelor’s or Master’s degree in Math, Statistics, Economics, Computer Science, or any other quantitative field.
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5+ years of experience with data integration, and database technologies, including NoSQL, SQL Server, Azure SQL DB, Postgres, Cosmos DB’s etc.
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5+ years of experience with Azure Cloud PaaS/SaaS solutions and managed services serverless technologies, including Azure Data Factory, Synapse Analytics and ADLS
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5+ years of experience in a role encompassing industry standard ETL development techniques and implementation of end-to-end data pipelines.
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Experience with data analysis and profiling of source data while developing or
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Experience in data warehousing methodologies and dimensional data modeling.
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Experience working with Azure DevOps code repositories and continuous integration and continuous delivery.
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Hands-on experience with Azure Data Engineering Stack - ADF, Synapse, SQL, Data Lakehouse, Python Notebooks, Microsoft Fabrics
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Hands on knowledge of data validation, cleansing, transformation, consolidation, de-duplication, aggregation, de-aggregation, and enrichment
Preferred:
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Coding experience: Python, C#, PowerShell for Data analysis purpose
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Experience with reporting data visualization tools such as Power BI or Tableau
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Exposure to MDM and metadata management including data catalogs using Microsoft Purview
It will be a plus:
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Knowledge of HIPAA and SOC2
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HealthCare domain knowledge
