| Urgent Requirement || Lead Azure Data Engineer || Fountain Valley, CA Hybrid || USC / GC Only at Valley, Alabama, USA |
| Email: [email protected] |
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Hi Hope you are doing well. We are looking for Lead Azure Data Engineer to fill its Long-Term Contract position. If you are interested, please reach out to me on [email protected]/ 9732409524 to discuss more about the position. Role: Lead Azure Data Engineer Duration: 4-6+ months contract to hire Location: Fountain Valley, CA Hybrid Visa USC/GC Manager notes: Antech is building a new Data Engineering team, reporting under the (new) Director of Data Engineering and Governance. (There was no prior centralized role for data engineering and governance). They are working on building an Azure based data platform and migrating to cloud, using Azure Data Lake storage, Databricks and Azure Synapse Analytics. Reporting to Director Currently in planning phase to be in development by February. The Lead position will be involved in the build and support, building the initial cloud data. They are looking for an Azure expert with strong interpersonal collaboration. Ideally looking for someone who can work out of the Fountain Valley office. Key Responsibilities: Design, build, and maintain Azure-centric data pipelines to ensure efficient data flow across our multi-cloud and on-premises systems. Perform data transformations and manage data tables to support business intelligence, reporting, and data-driven decision-making. Design event-driven solutions to sequence and automate Azure-centric data pipelines. Write and optimize complex SQL queries, develop data models, and manage data tables to enable seamless analytics. Mentor and assist junior ETL and data model developers to ensure operation consistency project deliverables. Prepare summary reports on project progress and operational status to program director. Collaborate with data visualization teams to support accurate, timely insights and visualizations. Collaborate in developing and optimizing a data warehouse, primarily on Azure. Support AI/ML initiatives to enhance and support data processes, predictive modeling, and drive business value for business units. Key Qualifications: Technical Mastery: Strong proficiency in Azure Cloud Platform, particularly Databricks, Synapse Analytics, Data Factory and Data Lake Storage, Azure SQL, and multi-dimensional data warehouse methodology. ETL Proficiency: Experienced in building ETL (Extract, Transform, Load) workflows that support efficient data movement and processing in cloud environments. Familiarity with sourcing data from leading Saas providers and their API solutions such as Oracle Fusion Cloud ERP, Salesforce CRM and CSM, Workday HCM and relational databases like Oracle, MS SQL Server and Postgres. Data Transformation Skills: Deep understanding of data transformation techniques to ensure accuracy and performance across all systems. Cloud Infrastructure Knowledge: Proficiency with Azure cloud infrastructure management and best practices for data security, scalability, and cost efficiency. Analytical Problem-Solving: Ability to troubleshoot data issues and proactively improve processes to enhance data reliability. Code Optimization: Advanced skills in writing and optimizing complex Python, Java, JSON, Spark and SQL queries for better performance and throughput. Data Modeling Expertise: Proven experience developing efficient data models that support large-scale analytics. Reporting, Analytics and Visualization : Proficiency in Analytics and visualization tools like Power BI, Tableau and Oracle Analytics Cloud. Data Governance: Strong knowledge of data governance practices, including data quality, lineage, data at rest and in-transit security and role-based access control protocols. Collaborative Communication: Ability to work cross-functionally with data scientists, analysts, visualization teams and business users to deliver comprehensive insights. LIMS Familiarity : Familiarity with Laboratory Information Management Systems (LIMS) such as Sunquest Antrim and Sysmex MOLIS is a big plus. AI/ML Experience: Familiarity with applying machine learning models to data processes and enhancing data pipeline functionality. Daily Responsibilities: In this role, you'll be managing end-to-end data engineering and automation, ensuring the highest standards of data quality, efficiency, scalability and security. Your day-to-day will include: Pipeline Management: Oversee and refine data pipelines, ensuring data is collected, transformed, and stored accurately across all systems. This includes monitoring and troubleshooting pipelines to prevent data loss, downtime and improve efficiency. ETL Development: Build, maintain, and improve ETL workflows that support data integration from multiple sources, handling various data types and frequencies. This includes event-driven solutions to sequence and automate Azure-centric data pipelines. Data Modeling & Transformation: Collaborate with a Data Management team to design data models that align with business needs and perform data transformations to create usable data sets for analysis and reporting. SQL Query Optimization: Write, test, and optimize SQL queries to ensure efficient data retrieval and processing. Collaboration with Analytics Teams: Work closely with data scientists, analysts, and stakeholders to support data requests, visualization needs, and other analytics functions. Cloud Infrastructure Management: Monitor and manage an Azure Data Platform and collaborate on other cloud platforms (Oracle Cloud, AWS) to maintain scalability and ensure secure data access. Data Quality Assurance: Conduct regular quality checks, clean data sets, and implement data governance practices to maintain accuracy and reliability. Documentation & Reporting: Keep thorough documentation of data processes, configurations, and workflows. Provide regular updates on system performance and data availability to downstream users and program director. Innovation & Continuous Improvement: Stay up to date on industry trends, experiment with new data tools and techniques, and apply best practices to drive continuous improvement. AI/ML Integration: Support AI/ML initiatives to enhance and support data processes, predictive modeling, and drive business value for business units. -- Keywords: artificial intelligence machine learning business intelligence information technology green card microsoft California Urgent Requirement || Lead Azure Data Engineer || Fountain Valley, CA Hybrid || USC / GC Only [email protected] |
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| 11:00 PM 28-Jan-25 |