Database Engineer

About the role: As a Data Engineer, you will play a key role in the Data Services Team, contributing to the development and maintenance of robust data infrastructure, products, and solutions. The Data Service team is responsible for delivering high-quality data via our service platform. Some of our key delivery channels are via FTPs, APIs, cloud storage like S3, data portals, and more. The Data Engineer's role is to provide solutions that involve managing the company’s historical data sources, availability, and data consistency. Furthermore, the role involves working with huge data extractions, data pipelines, schemas, partitions, indexes, performing corrections, and data migration operations, and most importantly these operations should be automated.

Job responsibilities: • Understanding and asking the right questions to begin the discovery process of the problem and solution. • Manage and maintain historical databases, ensuring data accuracy, reliability, and optimal performance. • Develop and implement robust data pipelines to efficiently process and transform large datasets. • Collaborate with cross-functional teams to understand data requirements and design solutions that meet business needs. • Utilize Python programming knowledge to create and maintain data integration scripts, tools and packages. • Implement and optimize ETL processes for seamless data flow within the organization using tools like Pentaho and/or Airflow. • Stay abreast of advancements in cloud technology and leverage cloud platforms for scalable and secure data storage and processing. • Design, construct, install, and maintain relational databases to support data storage and retrieval needs. • Troubleshoot and resolve data-related issues, ensuring data integrity throughout the entire lifecycle. • Write complex SQL queries on tables with millions of records and ensure data integrity. • Design Test Cases and write python/SQL scripts to validate data integrity and identify gaps and opportunities in our data pipelines. • Run Test Cases in order to ensure each functionality has been developed according to specifications and product needs.

Qualifications: • Bachelor’s degree in computer science, Information Technology, or a related field. • Proven experience as a Data Engineer or in a similar role. • Proficient in building and maintaining data pipelines for efficient data processing using tools like Pentaho, Airflow, etc. • Familiarity with relational database systems (e.g., MySQL, PostgreSQL) and database queries (e.g., DDL, DML, DQL, etc). • Strong proficiency in Python programming for data manipulation and analysis. • Solid understanding of data modeling, database design, ACID concepts, and data warehousing technology. • Hands-on experience with cloud technologies, such as AWS, and services like Athena, Glue, Aurora, and S3 would be an asset. • Excellent problem-solving skills and attention to detail. • Strong communication skills to collaborate effectively with team members and stakeholders. • Ability to adapt to evolving technologies and stay current with industry trends in data engineering. • Strong English skills should be required.

Morningstar’s hybrid work environment gives you the opportunity to work remotely and collaborate in-person each week. We’ve found that we’re at our best when we’re purposely together on a regular basis, at least three days each week. A range of other benefits are also available to enhance flexibility as needs change. No matter where you are, you’ll have tools and resources to engage meaningfully with your global colleagues.