| Azure Data Engineer USC GC EAD Only at Remote, Remote, USA |
| Email: [email protected] |
| Hello, Hope you are doing well! Suryaprakash [email protected] Greetings from Sapphire Software Solutions Inc., As a global staff augmentation company, Sapphire Software Solutions offers comprehensive workforce solutions and a large pool of personnel available on demand. If you have someone available for the following role, do let me know: Title: Azure Data Engineer Must-Haves (Concepts & Tools): Bachelors Degree (preferably in information technology, engineering, math, computer science, analytics, engineering or other related field) Minimum of 5+ years of combined experience in data engineering, ingestion, normalization, transformation, aggregation, structuring, and storage Minimum of 5+ years of combined experience working with industry standard relational, dimensional or non-relational data storage systems Minimum of 5+ years of experience in designing ETL/ELT solutions using tools like Informatica, DataStage, SSIS , PL/SQL, T-SQL, etc. Minimum of 5+ years of experience in managing data assets using SQL, Python, Scala, VB.NET or other similar querying/coding language Minimum of 3+ years of experience working with healthcare data or data to support healthcare organizations Project Scope / Components: High-Level Individual Duties: Support the full data engineering lifecycle including research, proof of concepts, design, development, testing, deployment, and maintenance of data management solutions Utilize knowledge of various data management technologies to drive data engineering projects Lead data acquisition efforts to gather data from various structured or semi-structured source systems of record to hydrate client data warehouse and power analytics across numerous health care domains Leverage combination of ETL/ELT methodologies to pull complex relational and dimensional data to support loading DataMarts and reporting aggregates. Eliminate unwarranted complexity and unneeded interdependencies Detect data quality issues, identify root causes, implement fixes, and manage data audits to mitigate data challenges Implement, modify, and maintain data integration efforts that improve data efficiency, reliability, and value Leverage and facilitate the evolution of best practices for data acquisition, transformation, storage, and aggregation that solve current challenges and reduce the risk of future challenges Effectively create data transformations that address business requirements and other constraints Partner with the broader analytics organization to make recommendations for changes to data systems and the architecture of data platforms Support the implementation of a modern data framework that facilitates business intelligence reporting and advanced analytics Prepare high level design documents and detailed technical design documents with best practices to enable efficient data ingestion, transformation and data movement. Leverage DevOps tools to enable code versioning and code deployment. Leverage data pipeline monitoring tools to detect data integrity issues before they result into user visible outages or data quality issues Leverage processes and diagnostics tools to troubleshoot, maintain and optimize solutions and respond to customer and production issues Continuously support technical debt reduction, process transformation, and overall optimization Leverage and contribute to the evolution of standards for high quality documentation of data definitions, transformations, and processes to ensure data transparency, governance, and security Ensure that all solutions meet the business needs and requirements for security, scalability, and reliability This email is generated using CONREP software. A10980 Keywords: procedural language |
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| Fri Feb 16 14:47:00 UTC 2024 |