Data Engineer

Job Summary We are looking for a Data Engineer to join our Data & Analytics team. This role is ideal for someone with at least 7-10 years of experience as Data Engineer who is eager to learn, contribute, and grow into a strong data engineering professional. The successful candidate will have strong skills in SQL and Python, be familiar with ETL concepts, and have the ability to work with stored procedures in SQL Server. Exposure to Snowflake and Tableau is a plus. Experience in AI/ML concepts or projects will also be considered a plus. Reporting to: Senior Data Engineer Key Responsibilities Develop, optimize, and maintain SQL Server stored procedures, views, and queries. Design, build, and maintain ETL/ELT pipelines to move and transform data from multiple sources. Write and maintain Python scripts for data wrangling, automation, and reporting. Ensure data quality, integrity, and consistency across platforms. Collaborate with analysts and business stakeholders to analyze and interpret data. Assist in data warehouse development and pipeline optimization within Snowflake. Document technical processes, workflows, and best practices. Qualifications Bachelor's degree in Computer Science, Information Systems, Data Analytics, or equivalent experience. Strong proficiency in SQL, with the ability to write and troubleshoot complex queries. Hands-on experience with Python for data processing and automation. Skilled in ETL concepts, data modeling, and data management best practices. Knowledge of SQL Server stored procedures and optimization techniques. Familiarity with Snowflake or other cloud-based data warehouses (a plus). Experience with Tableau or other BI tools (a plus). Strong analytical and problem-solving skills with attention to detail. Excellent communication and collaboration skills. Preferred Experience Exposure to cloud platforms such as AWS, Azure, or GCP. Experience with Git or other version control systems. Exposure to AI/ML concepts, frameworks, or projects (a plus). Understanding of data governance and documentation best practices. #J-18808-Ljbffr