Data Engineer

Job Description

As a Data Engineer, you will be responsible for designing, implementing, and maintaining scalable data pipelines and infrastructure for the collection, storage, and analysis of large volumes of data. You will collaborate with cross-functional teams to understand data requirements, develop data models, and ensure data quality and integrity. Your role will also involve optimizing and tuning data systems for performance and reliability. Requirements : Bachelors degree in computer science, Engineering, or a related field. Proven experience as a Data Engineer or similar role, with a strong background in data processing, storage, and analysis. Proficient in SQL and other languages such as SQL, Python, for building data pipelines. Experience with big data technologies such as Spark, Kafka, and NoSQL databases. Familiarity with cloud platforms (e.g., AWS, Azure) and their data services. Knowledge of data modeling techniques and database design principles. Experience with optimization of SQL queries/ETL pipelines. Strong problem-solving skills and attention to detail. Excellent communication and collaboration skills to work effectively in a cross-functional team environment. Ability to prioritize and manage multiple tasks in a fast-paced environment. Certification in relevant technologies (e.g., AWS Certified Big Data - Specialty) is a plus. Technical Skillset: Must have 4-6 years of ETL Data Engineer Minimum 2 years in AWS Cloud Data Engineer Role Must have Datawarehouse data modelling knowledge and experience. Programming Skills in Python & Pyspark Skilled in AWS Glue, AWS Lake Formation, AWS Redshift, AWS Athena, AWS Glue Crawlers & AWS Glue Data Catalog, AWS SNS & AWS Step Functions Stream pipeline implementation is value added. Must have 2+ years’ experience in BI tools (AWS Quick sight/Qlik Sense/Tableau/Power BI..) AWS Quick sight experience is valuable.