Data Scientist (Data & AI Engineer)

2 or more years of work experience with a Bachelor’s Degree or an Advanced Degree 3 or more years of work experience with a Bachelor’s Degree or more than 2 years of work experience with an Advanced Degree 3+ years of work experience with a bachelor’s degree in the STEM field. Strong experience with SQL, Python, Hadoop, Spark, Hive, Airflow and MPP data bases 5+ years of analytics experience with a focus on data Engineering and AI Experience with traditional data warehousing tools and techniques as well as modern technologies Advanced knowledge of SQL Solid understanding of best practices in data warehousing, ETL, data modeling, and data architecture. Experience with NoSQL databases Experience with cloud-based data warehousing and data pipeline management (AWS, GCP, Azure) Experience in Python, Spark, and exposure to scheduling tools like Tuber/Airflow is preferred. Able to create data dictionaries, setup and monitor data validation alerts, and execute periodic jobs. Experience with visualization software (e.g., Tableau, QlikView, PowerBI) is a plus. A team player and collaborator.

Design, develop, and maintain scalable data pipelines and systems. Monitor and troubleshoot data pipeline issues. Establish data processes and automation. Deliver data engineering and Machine learning projects. Setup ML Ops pipelines and Gen AI pipelines. Collaborate with cross-functional teams to ensure data quality. Provide expertise in data warehousing, ETL, and data modeling. Extract and manipulate large datasets using standard tools. Develop data solutions using Agile principles. Provide ongoing production support. Communicate complex concepts clearly. Stay up to date with data engineering trends and technologies.