01Responsibilities
Analyses current business practices, processes, and procedures as well as identifying future business opportunities for leveraging Microsoft Azure Data & Analytics Services.Provide technical leadership and thought leadership as a senior member of the Analytics Practice in areas such as data access & ingestion, data processing, data integration, data modeling, database design & implementation, data visualization, and advanced analytics.Engage and collaborate with customers to understand business requirements/use cases and translate them into detailed technical specifications.Develop best practices including reusable code, libraries, patterns, and consumable frameworks for cloud-based data warehousing and ETL.Maintain best practice standards for the development or cloud-based data warehouse solutioning including naming standards.Designing and implementing highly performant data pipelines from multiple sources using Apache Spark and/or Azure DatabricksIntegrating the end-to-end data pipeline to take data from source systems to target data repositories ensuring the quality and consistency of data is always maintainedWorking with other members of the project team to support delivery of additional project components (API interfaces)Evaluating the performance and applicability of multiple tools against customer requirementsWorking within an Agile delivery / DevOps methodology to deliver proof of concept and production implementation in iterative sprints.Integrate Databricks with other technologies (Ingestion tools, Visualization tools).Proven experience working as a data engineerHighly proficient in using the spark framework (python and/or Scala)Extensive knowledge of Data Warehousing concepts, strategies, methodologies.Direct experience of building data pipelines using Azure Data Factory and Apache Spark (preferably in Databricks).Hands on experience designing and delivering solutions using Azure including Azure Storage, Azure SQL Data Warehouse, Azure Data Lake, Azure Cosmos DB, Azure Stream AnalyticsExperience in designing and hands-on development in cloud-based analytics solutions.Expert level understanding on Azure Data Factory, Azure Synapse, Azure SQL, Azure Data Lake, and Azure App Service is required.Designing and building of data pipelines using API ingestion and Streaming ingestion methods.Knowledge of Dev-Ops processes (including CI/CD) and Infrastructure as code is essential.Thorough understanding of Azure Cloud Infrastructure offerings.Strong experience in common data warehouse modeling principles including Kimball.Working knowledge of Python is desirableExperience developing security models.Databricks & Azure Big Data Architecture Certification would be plusMandatory skill sets:ADE, ADB, ADFPreferred skill sets:ADE, ADB, ADFYears of experience required:8-13 YearsEducation qualification:BE, B.Tech, MCA, M.TechaEducation (if blank, degree and/or field of study not specified)Degrees/Field of Study required: Bachelor of Engineering, Master of EngineeringDegrees/Field of Study preferred:Certifications (if blank, certifications not specified)Required SkillsAndroid Debug Bridge
