Data Engineer

1 week ago


chennai district, India KaarTech Full time

Key Responsibilities · Data Pipeline Development: Design, develop, and maintain scalable data pipelines to support various data analytics and reporting needs. · Data Integration: Integrate data from multiple sources and ensure data quality and consistency. · Data Modelling: Build and optimize data models using Spark to support complex data transformations and analysis. · SQL Development: Write efficient SQL queries to extract, transform, and load data into data warehouses and other storage solutions. · Big Data Processing: Utilize big data technologies, especially Apache Spark, to process and analyze large datasets. · Cloud Services: Implement and manage data solutions on cloud platforms such as Azure, AWS, or GCP. · Problem Solving: Analyze and resolve data-related issues, ensuring data accuracy and reliability. · Collaboration: Work closely with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions. Required Skills and Qualifications · Education: Bachelor’s degree in Computer Science, Information Technology, or a related field. · Experience: 3 to 5 years of experience in data engineering or a related role. · Programming: Proficient in Python, with experience in data manipulation and automation scripts. · Big Data: Strong knowledge of big data technologies, especially Apache Spark. · SQL: Excellent skills in writing and optimizing SQL queries. · Data Modelling: Experience in data modelling and data architecture, particularly using Spark. · Cloud Platforms: Hands-on experience with at least one cloud platform (Azure, AWS, GCP). · Data Analytics Concepts: Solid understanding of data engineering and analytics concepts. · Problem Solving: Strong problem-solving skills with the ability to troubleshoot data issues effectively. · Communication: Good communication skills, with the ability to work collaboratively in a team environment. Preferred Qualifications · Databricks: Experience with Databricks tool is a plus but not mandatory. · Certifications: Certifications in Databricks or Azure (or any relevant certifications) are highly



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