Job
Description
We are seeking an experienced Data Engineer to design, develop, and optimize data pipelines, workflows, and integrations across enterprise platforms. The ideal candidate will have a strong background in SQL, Data Warehousing (DWH), Azure, and ETL tools , along with experience handling large-scale data processing and cloud-based data solutions . Key Responsibilities: Implement data structures, workflows, and integrations to ensure seamless and accurate business process execution. Collaborate with architects, client leads, and technology teams to define and develop data pipelines . Develop and maintain scalable data pipelines and build new API integrations to support growing data needs. Analyze source data and create data mappings for efficient data transformations. Optimize database performance , ensuring efficient query execution and scalability. Design, implement, and manage data warehouses, databases, tables, and SQL queries to power reporting tools like Tableau . Write complex and efficient SQL queries to transform raw data into structured models for analytics. Work closely with analytics, data science, and engineering teams to automate data analysis, enhance data visualization , and improve data transformation processes. Utilize Azure Data Lake (ADL), Azure Data Factory (ADF), and DBT to curate and process data into meaningful insights. Provide technical guidance to junior team members, assist with client interactions, and manage task allocation and reporting. Required Qualifications & Skills: Engineering Degree (BE/BTech/MCA/BCA/BSc IT) or equivalent. Proven experience as a Data Engineer with hands-on expertise in SQL, Data Warehousing (DWH), Azure, Azure Data Lake (ADL), Azure Data Factory (ADF), and Snowflake . Strong understanding of ETL tools such as SSIS or DataStage . Preferred Skills (Desirable but Not Mandatory): Experience in Big Data technologies such as Hive, Impala, and Spark .
