Engineer 3 || Data

The ideal candidate should have 3-5 years of experience in implementing scalable and sustainable data engineering solutions using tools such as Databricks, Snowflake, Teradata, Apache Spark, and Python. Your responsibilities will include creating, maintaining, and optimizing data pipelines as workloads transition from development to production for specific use cases. You will be responsible for end-to-end development, including coding, testing, debugging, and deployment. Automation is key, and you will drive the use of modern tools and techniques to automate repetitive data preparation and integration tasks to enhance productivity. You will be mapping data between source systems, data warehouses, and data marts, as well as training counterparts in data pipelining and preparation techniques. Collaboration is essential, and you will interface with other technology teams to extract, transform, and load data from various sources. You will also play a crucial role in promoting data and analytics capabilities to business unit leaders, educating them on leveraging these capabilities to achieve their business goals. You should be proficient in converting SQL queries into Python code running on a distributed system and developing libraries for code reusability. An eagerness to learn new technologies in a fast-paced environment and excellent communication skills are essential for this role. Experience with data pipeline and workflow management tools such as Rundeck and Airflow, AWS cloud services like EC2, EMR, RDS, Redshift, and stream-processing systems like Spark-Streaming would be advantageous.,