Job Description
Job description
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
