Azure Data Engineer

5 days ago

India Y&L Consulting, Inc. Full time

Skills

       Azure Data Factory, Azure Data Lake, Azure SQLData Warehouse, Azure Databricks, Azure Synapse, Spark, Python, Azure AnalysisServices, Azure DevOps

       Experience working in ETL process for at least 8 years

       Experience developing ETL process using AzureETL tools for at least 5 years


Qualifications

       Bachelor’s degree in information systems,Computer Science, Engineering, or related field

       Proficient in designing and implementing datasourcing and transformation processes (ETL) in a large, distributed environmentusing cloud services e.g., Azure Data Factory,Azure Data Lake, Azure SQL Data Warehouse, Azure Databricks, Azure Synapse,Spark, Python, Azure Analysis Services and Azure DevOps

       Hands-on experience with developing complex ETLpipelines that ingest and transform data from various source systems into Azurecloud operational databases and data warehouse environment

       Proficient in developing and operationalizingvarious data distribution patterns such as APIs, event based, publish/subscribemodels

       Well versed with data models, source targetdefinitions, identify/fixing discrepancies adhering to enterprise datagovernance standards

       Adept with Azure DevOps-CI/CD (ContinuousIntegration and Continuous Deployment) and Test-Driven Development practices

       Design, develop and implement scalable batch /real-time data pipelines to integrate data from a variety of sources into anAzure database / data warehouse and data lake

       Experience migrating data lakes from on-premisesto cloud

       Experience with agile delivery using AzureDevOps

       Experience monitoring performance of dataworkflows and infrastructure through use of monitoring tools and enablingalerts

       Functional knowledge of data visualization tools




Responsibilities

       Design and implement data frameworks andpipelines to process data from on-premises and cloud data sources to feed intothe Azure Cloud, monitor data quality and implement related controls

       Evaluate existing designs, improve methods, andimplement optimizations

       Analyze and validate data sharing requirementswithin and outside data partners

       Analyze and interpret collected data;identifying trends; writing reports and recommendations for internal orexternal clients

       Use statistical practices to analyze current andhistorical data to make predictions, identify risks, and opportunities enablingbetter decisions on planned/future events

       Work with business leadership to understand datarequirements; propose and develop solutions that enable effectivedecision-making and drive business objectives

       Prepare project deliverables that are valued bythe business and present them in such a manner that they are readily understoodby project stakeholders

       Prepare advanced project implementation plansusing Agile methodologies, which highlight milestones and deliverables,leveraging standards, practices, and work planning tools

       Recognize potential issues and risks during theanalytics project implementation and recommend mitigation strategies

       Document best practices for data analysis, dataengineering, and evangelize their usages

       Work with stakeholders, including the executivesas well as product engineering teams to assist with data-related technicalissues and support their data infrastructure needs

       Create data tools for data scientist team toassist them in building and optimizing our product into an innovative industryleader

       Work with data and analytics experts to strivefor greater functionality in our data capabilities

       Experience inoffshore/ onsite coordination



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