Data Engineer (Azure Or AWS)

You will be responsible for architecting data warehousing and business intelligence solutions to address cross-functional business challenges. This will involve interacting with business stakeholders to gather requirements and deliver comprehensive Data Engineering, Data Warehousing, and analytics solutions. Additionally, you will collaborate with other technology teams to extract, transform, and load data from diverse sources. You should have a minimum of 5-8 years of end-to-end Data Engineering Development experience, preferably across industries such as Retail, FMCG, Manufacturing, Finance, Oil & Gas. Experience in functional domains like Sales, Procurement, Cost Control, Business Development, and Finance is desirable. You are expected to have 3 to 10 years of experience in data engineering projects using Azure or AWS services, with hands-on expertise in data transformation, processing, and migration using various tools such as Azure Data Lake Storage, Azure Data Factory, Databricks, AWS Glue, Redshift, and Athena. Familiarity with MS Fabric and its components will be advantageous, along with experience in working with different source/target systems like Oracle Database, SQL Server Database, Azure Data Lake Storage, ERP, CRM, and SCM systems. Proficiency in reading data from sources via APIs/Web Services and utilizing APIs to write data to target systems is essential. You should also have experience in Data Cleanup, Data Cleansing, and optimization tasks, including working with non-structured data sets in Azure. Knowledge of analytics tools like Power BI and Azure Analysis Service, as well as exposure to private and public cloud architectures, will be beneficial. Excellent written and verbal communication skills are crucial for this role. Ideally, you hold a degree in M.Tech / B.E. / B.Tech (Computer Science, Information systems, IT) / MCA / MCS. Key requirements include expertise in MS Azure Data Factory, Python, PySpark Coding, Synapse Analytics, Azure Function Apps, Azure Databricks, AWS Glue, Athena, Redshift, and Databricks Pysark. Exposure to integration with various applications/systems like ERP, CRM, SCM, WebApp using APIs, Cloud, On-premise systems, DBs, and file systems is expected. The role necessitates a minimum of 3 Full Cycle Data Engineering Implementations (5-10 years of experience) with a focus on building data warehouses and implementing data models. Exposure to the consulting industry is mandatory, along with strong verbal and written communication skills. Your primary skills should encompass Data Engineering Development, Cloud Engineering with Azure or AWS, Data Warehousing & BI Solutions Architecture, Programming (Python PySpark), Data Integration across various systems, Consulting experience, ETL and Data Transformation, and knowledge in Cloud Architecture. Additionally, familiarity with MS Fabric, handling non-structured data, Data Cleanup and Optimization, API/Web Services, Data Visualization, and industry and functional knowledge will be advantageous. The compensation package ranges from INR 12-28 lpa, subject to the candidate's performance and experience level.,