Data Engineer

The Role:
In this role, you will take responsibility for developing automated data processing, maintaining, testing, and optimizing data pipelines that enable the end-to-end data flow of Morningstar Data Dictionary through our data platform. You are also responsible for ensuring quality of data processing that includes data security, fault tolerance, performance, scale and event based operational engineering processes. The ideal candidate will have a passion for data, metadata driven solution design and secured data processing technology, operating in Public Cloud platform. Also, candidate should demonstrate excellent problem solving, communication and a good understanding of financial investment data. Understanding data lineage management using metadata is a plus. Your track record for establishing best engineering practices, applying innovation and data pipeline management to make solid design decisions sets you apart from your peers.

 

Job responsibilities:

• Hands-on data cleaning, wrangling and preparation for Morningstar Data Dictionary content release.
• Maintain and optimize data pipelines for Morningstar Data Dictionary product through our data platform.
• Automate data workflows such as data ingestion, aggregation, and ETL processing.
• Contribute to dataset physical schema enhancements with attribute management using metadata requirements to support various use cases (for example taxonomy, data lineage, etc.)
• Partner with architect, quality assurance (QA), and business analyst (BA) to identify opportunities to improve current Morningstar Data Dictionary release process, as well as to deliver other projects according to requirements, in collaboration with program and product management, technology leadership and development teams

 

Qualifications:

• Advanced SQL skills and experience with various relational database management systems (e.g. MySQL, PostgreSQL, MS SQL, etc.)
• Experience in test driven development (TDD) practice
• Experience in container (e.g., Docker) based solution development
• Experience in applying and implementing authorization and encryption in data processing and storage level as part ETL
• Experience in physical database schema design
• 3+ years of experience with Python
• Hands-on experience with ETL tools, along with configuration driven data transformation development
• Experience with public cloud infrastructure, primarily Amazon Web Services (AWS)
• Self-motivated, excellent work ethic, strong interpersonal and communication skills
• Ability to work independently and in a team environment
• Ability to communicate complex ideas, problems and solutions in ways that are consumable by different audiences in both written and spoken manner
• Excellent problem-solving skills

 

Nice to have:

• Possess Bachelor's degree in Computer Science, Information Systems, Engineering or related field of study
• Good understanding of NoSQL databases (e.g. MongoDB, etc)
• Experience in Java programming language and framework
• Experience with working on large datasets

Morningstar is an equal opportunity employer.

The Role:
In this role, you will take responsibility for developing automated data processing, maintaining, testing, and optimizing data pipelines that enable the end-to-end data flow of Morningstar Data Dictionary through our data platform. You are also responsible for ensuring quality of data processing that includes data security, fault tolerance, performance, scale and event based operational engineering processes. The ideal candidate will have a passion for data, metadata driven solution design and secured data processing technology, operating in Public Cloud platform. Also, candidate should demonstrate excellent problem solving, communication and a good understanding of financial investment data. Understanding data lineage management using metadata is a plus. Your track record for establishing best engineering practices, applying innovation and data pipeline management to make solid design decisions sets you apart from your peers.

 

Job responsibilities:

• Hands-on data cleaning, wrangling and preparation for Morningstar Data Dictionary content release.
• Maintain and optimize data pipelines for Morningstar Data Dictionary product through our data platform.
• Automate data workflows such as data ingestion, aggregation, and ETL processing.
• Contribute to dataset physical schema enhancements with attribute management using metadata requirements to support various use cases (for example taxonomy, data lineage, etc.)
• Partner with architect, quality assurance (QA), and business analyst (BA) to identify opportunities to improve current Morningstar Data Dictionary release process, as well as to deliver other projects according to requirements, in collaboration with program and product management, technology leadership and development teams

 

Qualifications:

• Advanced SQL skills and experience with various relational database management systems (e.g. MySQL, PostgreSQL, MS SQL, etc.)
• Experience in test driven development (TDD) practice
• Experience in container (e.g., Docker) based solution development
• Experience in applying and implementing authorization and encryption in data processing and storage level as part ETL
• Experience in physical database schema design
• 3+ years of experience with Python
• Hands-on experience with ETL tools, along with configuration driven data transformation development
• Experience with public cloud infrastructure, primarily Amazon Web Services (AWS)
• Self-motivated, excellent work ethic, strong interpersonal and communication skills
• Ability to work independently and in a team environment
• Ability to communicate complex ideas, problems and solutions in ways that are consumable by different audiences in both written and spoken manner
• Excellent problem-solving skills

 

Nice to have:

• Possess Bachelor's degree in Computer Science, Information Systems, Engineering or related field of study
• Good understanding of NoSQL databases (e.g. MongoDB, etc)
• Experience in Java programming language and framework
• Experience with working on large datasets

Morningstar is an equal opportunity employer.

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.