| Lead Sr Azure Data Engineer||Hybrid||CITIZEN,GREEN CARD at Minneapolis, Minnesota, USA |
| Email: [email protected] |
| From: Aditya Nath Kaushal, vyze [email protected] Reply to: [email protected] Job Description - Job Title: Lead/Sr Azure Data Engineer Location : Minneapolis, MN - Hybrid Duration: 6+ Months MOI: Skype PV Response after reviewing previous candidate : Focus on finding a true Lead Engineer, with strong experience in Azure Synapse, and Azure Data Engineering services. Candidates with 8-10 total years of experience are falling short in understanding bigger picture, not lead level enough, they can complete the coding but not explain the overall process in detail. HM wants 12+ year types that can code and understand/explain end-end to deliver solutions without hand-holding. These two candidates could not deliver their experience confidently. If needed look for 15+ year type profiles, those that have moved out of being a senior engineer and into purely Lead roles. Interview Process: One/Done Video Interview with Live Coding Will be asked to load data into Azure Synapse environment. Will be asked to use Visual Studio Code (VSCode) for coding, must have access to an account in portal.azure.com and setup Synapse workspace that includes ADLS Gen 2 storage. Candidate Feedback thus far: Candidates with 8-10 total years of experience are falling short in understanding bigger picture, not lead level enough, they can complete the coding but not explain the overall process in detail. HM wants 12+ year types that can code and understand/explain end-end to deliver solutions without hand-holding. ** Do not share candidate with less than 12 years overall experience, HM wont bite on them!!! ** Must Haves: 12+ years in Data Engineering, focused in Azure 5+ years in Sr/Lead capacity Expert in Python, Apache Spark, Azure Synapse, and Azure Data Engineering services Position Overview We are seeking a Lead Developer with advanced skills in Python, Apache Spark, Azure Synapse, and Azure Data Engineering services to develop and manage ETL pipelines and data processing solutions that support AI/ML initiatives. The ideal candidate will have strong expertise in Azure Cloud, including SQL, Data Factory, SQL Pools, Spark Pools, and Data Warehousing. A background in CI/CD processes, cross-functional collaboration, and methodologies is essential. In addition, knowledge of Data Science, Java, Kubernetes, Azure Data Lake Storage (ADLS) Gen2, and API development is required. Key Responsibilities 1. ETL and Data Pipeline Development - Design, develop, and optimize scalable ETL processes using Python, Apache Spark, and Azure Synapse. - Build and manage Azure Data Factory pipelines to orchestrate complex data workflows. - Use SQL Pools and Spark Pools within Synapse to manage and process large datasets efficiently. - Implement Data Warehousing solutions using Azure Synapse Analytics to provide structured and queryable data layers. - Ensure the data platform supports real-time and batch AI/ML data requirements. 2. Azure Cloud Development & CI/CD Deployment - Build, configure, and manage CI/CD pipelines on Azure DevOps for ETL and data processing tasks. - Automate infrastructure provisioning, testing, and deployment using Infrastructure-as-Code (IaC) tools like ARM templates or Terraform. - Optimize Azure Data Lake Storage (ADLS Gen2) to store and manage raw and processed data efficiently, ensuring proper access control and data security. 3. Cross-Functional Collaboration - Collaborate with Data Scientists, Data Engineers, ML Engineers, and Business Analysts to translate business requirements into data solutions. - Work with the DevOps and Security teams to ensure smooth and secure deployment of applications and pipelines. - Act as the technical lead in designing, developing, and implementing data solutions, mentoring junior team members. 4. Data Engineering and API Development - Develop and integrate with external and internal APIs for data ingestion and data exchange. - Build, test, and deploy RESTful APIs for secure data access. - Use Kubernetes for containerizing and deploying data processing applications. - Manage data storage and transformation to support advanced Data Science and AI/ML models. 5. Agile Project Management - Participate in and lead Agile ceremonies, such as sprint planning, daily stand-ups, and retrospectives. - Collaborate with cross-functional teams in iterative development to ensure high-quality and timely feature delivery. - Adapt to changing project priorities and business needs in an Agile environment. Required Skills and Qualifications 1. Technical Skills: - Expertise in Python and Apache Spark for large-scale data processing. - Strong experience in Azure Synapse Analytics, including SQL Pools and Spark Pools. - Advanced proficiency in Azure Data Factory for ETL pipeline orchestration and management. - Knowledge of Data Warehousing principles, with hands-on experience building solutions on Azure. - Experience with SQL, including complex queries, optimization, and performance tuning. - Familiarity with CI/CD tools like Azure DevOps and managing infrastructure in Azure Cloud. - Experience in Java for API integration and microservices architecture. - Hands-on knowledge of Kubernetes for containerized data processing environments. - Proficiency in working with Azure Data Lake Storage (ADLS) Gen2 for data storage and management. - Experience working with APIs (REST, SOAP) and building API-based data integrations. 2. Agile and Cross-Functional Skills: - Experience working in an Agile environment, using Scrum or Kanban. - Ability to lead, mentor, and coach junior developers in the team. - Strong collaboration skills to work with data scientists, analysts, and cross-functional teams to deliver end-to-end data solutions. 3. Behavioral Skills: - Strong analytical and problem-solving skills with a passion for data-driven solutions. - Excellent communication and presentation skills, able to explain complex technical concepts to non-technical stakeholders. - Ability to work in a fast-paced, dynamic environment with changing priorities. - Self-motivated and results-oriented with attention to detail. Preferred Qualifications - Azure certifications in data engineering or cloud architecture. - Experience deploying AI/ML models on cloud platforms. - Familiarity with Data Governance best practices, ensuring compliance with data privacy regulations. Keywords: continuous integration continuous deployment artificial intelligence machine learning Minnesota Lead Sr Azure Data Engineer||Hybrid||CITIZEN,GREEN CARD [email protected] |
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| Thu Nov 14 05:15:00 UTC 2024 |