Data Engineer

As a Data Engineer, you will be responsible for leading the design, development, and implementation of scalable data pipelines and ELT processes using tools like Databricks, DLT, dbt, Airflow, and others. Your role will involve collaborating with stakeholders to understand data requirements, optimizing existing data pipelines, and ensuring data quality, reliability, and performance. Additionally, you will develop and enforce data engineering best practices, mentor junior data engineers, and stay updated with industry trends to recommend improvements. To qualify for this position, you should have a Bachelor's degree in Computer Science, Information Technology, Management Information Systems (MIS), Data Science, or a related field, along with at least 7 years of experience in data engineering and/or architecture focusing on big data technologies. You must possess extensive production experience with Databricks, Apache Spark, and other related technologies, as well as familiarity with orchestration and ELT tools like Airflow, dbt, etc. Strong SQL knowledge, proficiency in programming languages such as Python, Scala, or Java, and a solid understanding of data warehousing concepts are essential. Experience with cloud platforms like Azure, AWS, Google Cloud, excellent problem-solving skills, and the ability to work in a fast-paced, collaborative environment are required. Moreover, you should have strong communication and leadership skills to effectively mentor and guide team members. Preferred qualifications for this role include experience with machine learning and data science workflows, knowledge of data governance and security best practices, and certifications in Databricks, Azure, Google Cloud, or related technologies. If you meet the experience requirements, possess good communication skills, and have experience in Pyspark, we encourage you to apply for this position.,