Sr. Azure Data Engineer

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

�       Bachelors 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 coordinationRole & responsibilities

Preferred candidate profile

Perks and benefits