Job Description

The Group:Enterprise Data and Platform (ED&P) is a central service provider for Morningstar, including a central data system of collecting, storing, consolidating, normalizing, calculating, and distributing Morningstars high-quality data and capabilities to internal and external consumers. ED&P is both a data provider and business enabler. The individuals in this group enable faster business growth, better scale, and improve customer experience by maximizing full commercial and brand value of data sets in their entirety.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 for data products owned by Enterprise Data Governance 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, monitoring every process and routines and optimizing their performance.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 data products owned by Enterprise Data Governance 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.)Collaborate with architect, data engineer and quality assurance (QA) to identify opportunities to improve current Morningstar Data Dictionary content release process.Collaborate with product and project management, technology leadership, developer, and QA to deliver projects according to requirements.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) practiceExperience in container (e.g., Docker) based solution development.Experience in applying and implementing authorization and encryption in data processing and storage level as part ETLExperience in physical database schema design3+ years of experience with PythonHands-on experience with ETL tools, along with configuration driven data transformation developmentExperience with public cloud infrastructure, primarily Amazon Web Services (AWS)Self-motivated, excellent work ethic, strong interpersonal and communication skillsAbility 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 form.Excellent problem-solving skillsNice to havePossess Bachelor's degree in Engineering, or a related field of studyGood understanding of NoSQL databases (e.g. MongoDB, etc)Experience in Java programming language and frameworkExperience with working on large datasetsMorningstar is an equal opportunity employer.I10_MstarIndiaPvtLtd Morningstar India Private Ltd. (Delhi) Legal EntityMorningstars hybrid work environment gives you the opportunity to work remotely and collaborate in-person each week. Weve found that were at our best when were 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, youll have tools and resources to engage meaningfully with your global colleagues.

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