About the Role
The Group: Morningstar's Quantitative Research Group creates independent investment research and data-driven analytics designed to help investors and Morningstar achieve better outcomes by making better decisions. We utilize statistical rigor and large data sets to inform the methodologies we develop. Our research encompasses hundreds of thousands of securities within a large breadth of asset classes including equities, fixed income, structured credit, and funds. Morningstar is one of the largest independent sources of fund, equity, and credit data and research in the world, and our advocacy for investors' interests is the foundation of our company.
The Role: As a Senior Data Engineer, you will work along with Quant Researchers, Data Scientists to support all Data engineering initiatives. You will play a key role in data modeling and database architecture along with testing and maintaining data solutions(models)on the AWS platform. You are an individual who possesses strong technical skills with exposure to cloud technology, has good problem solving & consulting skills, and has an eye for picking up challenging opportunities. You also enjoy working with cross-functional technical teams on complex problems and are always looking to improve yourself and others around you.
Responsibilities:

• Build/ Support Data Engineering pipelines leveraging massive amounts of structured, unstructured financial/non-financial data.
• Build Data Models, Database Schemas and implement new data patterns.
• Research varied cloud/ AWS Tools (Microservices, Big Data & Batch Services) for building data pipelines to ingest massive amounts of big data.
• Program Python, Spark, AWS technologies to support varied data pipeline requests.
• Build and/or lead the creation and maintenance of optimal data pipelines and architectures.
• Stay abreast of industry trends and enable successful data solutions by leveraging best practices.
• Participate and provide Proof of Concepts (POCs) to demonstrate proposed solutions
• Enable team members in the data engineering space through training, culture, and team building.
• Assemble large, complex data sets that meet functional / non-functional business requirements.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using AWS 'big data' technologies.
• Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
• Work with data and analytics experts to strive for greater functionality in our data systems.

Qualifications

• Bachelor/Master/Engineering degree in IT/Computer Science/Software Engineering or relevant field
• 10+ years of total experience in a complex, technical environment
• Knowledge of data flow and architecture strategies is a plus
• Advanced knowledge and hands-on experience with python
• Experience building and optimizing data pipelines.
• Hands-on experience with evaluating, building and implementing data architecture patterns.
• Strong analytic skills related to working with unstructured datasets.
• Build processes supporting data transformation, data structures, metadata, dependency and workload management.
• A successful history of manipulating, processing and extracting value from large disconnected datasets.
• Working knowledge of message queuing, stream processing, and highly scalable 'big data' data stores.
• Actively handle escalated incidents to resolution and suggest solutions to limit future exposure
• Strong project management and organizational skills.
• Experience Leading, supporting and working with cross-functional teams in a dynamic environment.
• Experience with big data tools: Hadoop, Spark, Kafka, etc.
• Experience with relational SQL and NoSQL databases
• Experience with AWS cloud services: Glue, Lambda, EMR, RDS, Redshift
• Experience with stream-processing systems: Spark-Streaming, etc.
• Experience with object-oriented/object function scripting languages: Python etc.

Nice to have

• AWS Certification[Solution Architect/Data Analytics Specialty/Machine Learning Specialty] be a plus
• Advanced knowledge data management and data governance principles is a plus

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