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Senior Data Engineer
4 weeks ago
Primary Responsibilities:Use knowledge to architect data warehousing and BI solutions that solve problems that cut across multiple business functionsInteract with business customers, gathering requirements and delivering complete Data Engineering, Data Warehousing, and analytics solutions.Interface with other technology teams to extract, transform, and load data from a wide variety of data sourcesJob Requirements:Minimum 5-8 years of end-to-end Data Engineering Development experience – Total professional experience does not matter much. This is mainly for 5-10+ years experienced profiles.Worked extensively across different industry domain specially Retail, FMCG, Manufacturing, Finance, Oil & Gas, etc.Worked extensively across functional domains like Sales, Procurement, Cost Control, Business Development, Management Reporting, Finance, etc.3 to 10 years of experience in working on data engineering projects using Azure / AWS services.Extensive hands-on experience implementing data transformation, processing and data migration using Azure or AWS services: ADLS, Azure Data Factory, Databricks Azure Functions, Synapse/DW, Azure SQL DB, Event Hub, Azure Stream Analytics, Databricks, AWS Glue, Redshift, AthenaExposure to MS Fabric and its components is added advantage.Experience in working with different source/target systems like Oracle Database, SQL Server Database, Blob Storage, Azure Data Lake Storage, ERP, CRM, SCM systems.Ability to read data from sources using APIs/Web Services and having worked with API to write data to target systems.Experience with Data Cleanup, Data Cleansing, and optimization related exercises.Experience working with non-structured data sets in Azure will be an added advantage.Experience with other analytics tools like Power BI, Azure Analysis service would be an advantage.Experience with private and public cloud architectures.Excellent written and verbal communication skillsQualifications:M.Tech / B.E. / B.Tech (Computer Science, Information systems, IT) / MCA / MCSKey Requirements -MS Azure Data Factory, Python, PySpark Coding, Synapse Analytics, Azure Function Apps, Azure Databricks or AWS Services – Glue, Athena, Redshift, Databricks PysarkMS Fabric exposureIntegration to various applications/systems – ERP, CRM, SCM, WebApp using APIs, Cloud, On-premise systems, DBs, file systems.Min 3 Full Cycle Data Engineering Implementations (5-10 Yrs experience) with exposure to building data warehouses and implementing data models on projects.Exposure to consulting industry is a must.Excellent verbal and written communication skill.Must have skills:Data Engineering DevelopmentCloud Engineering with Azure or AWSData Warehousing & BI Solutions ArchitectureProgramming (Python PySpark)Data Integration across ERP CRM SCM WebApps databases and cloud or on -premise systemsConsulting experienceStrong communication skillsETL and Data Transformation (Azure Data Factor Databricks AWS Glue Redshift Athena)Secondary skills:MS FabricNon-structured Data ManagementData Cleanup and OptimizationAPI/Web Services experienceCloud Architecture Knowledge - Private and public cloudData Visualization (Power BI Azure Analysis Service)Industry Knowledge: Retail FMCG Manufacturing Finance Oil & GasFunctional Knowledge: Sales Procurement Cost Control Finance etcPackage – INR 12-28 lpa based on different experience level – However this is somewhat flexible/negotiable depending upon the candidate performance and experience.
