Data Engineer

Company Details

Midwest Employers Casualty (MEC) is a member of the W. R. Berkley Corporation, a fortune 500 company, rated A+ (Superior) by A.M. Best Company, based in Chesterfield, MO. We improve the quality of life for employees severely injured on the job and help companies understand and mitigate their risk for workers' compensation injuries. MEC has a friendly, results-focused work environment. We seek employees who take initiative, are quick to adapt, are dependable, and like working as part of a team.

https://www.mecasualty.com/

The company is an equal employment opportunity employer.

Responsibilities

The Data Engineer is responsible for designing, creating, deploying, and managing MEC's data architecture. The Data Engineer develops and maintains scalable data pipelines and build out new API integrations to support continuing increases in data volume and complexity. The role requires a deep understanding of analytics and database management to improve data reliability, efficiency, and quality.

Key functions include but are not limited to:

Design and Build Database Systems:

• Design, construct, install, test, and maintain highly scalable data management systems that meet both business requirements and industry best practices.

Data Modeling and Design:

• Design data models and architecture patterns that consider functionality, cost, performance, scalability, reusability, security, and extensibility.

• Design conceptual, logical, and physical data models to support business intelligence and analytics.

• Architect data structures that eliminate redundancies and integrate disparate unstructured and structured data sources into coherent enterprise data models.

• Create detailed data structure representations such as Entity-Relationship Diagrams (ERDs).

Data Strategy and Management:

• Develop and implement strategies for data acquisition, archival recovery, and database implementation, ensuring the optimization of data fidelity through cleansing and analysis.

• Perform data analysis, profiling, and validation to ensure accuracy and quality of data.

• Implement data governance and security measures to ensure data integrity and compliance with internal and regulatory standards.

Integration and Migration:

• Manage large datasets and maintain robust data from a wide array of source data systems (enterprise data warehouses, relational databases, APIs, document, unstructured data, big data, vector databases).

• Facilitate data migration from legacy systems to new solutions.

• Prepare data for prescriptive and predictive models.

Performance Management:

• Oversee and optimize data storage for all database systems and implement automated scripts for regular maintenance to enhance system performance.

Collaboration and Support:

• Collaborate with data scientists, analysts, and other departmental leaders to address data-related technical needs and provide ongoing support and training.

• Actively participate in agile scrum ceremonies, including daily stand-ups, sprint planning, retrospectives, and reviews.

Innovation and Research:

• Stay updated with the latest industry trends and technologies in data architecture, data engineering, and data management.

• Identify strategic data/workflow gaps/opportunities and advocate for new technologies and techniques.

Qualifications

• University or college degree in the field of computer science or equivalent experience.

• Proven experience as a Data Engineer, or a similar role in data management.

• Comprehensive knowledge of data warehousing, database design and data modeling, with strong expertise in SQL.

• Experience with cloud services like Microsoft Azure and proficiency in handling various database technologies including SQL.

• Experience integrating external data providers.

• Excellent analytical skills, with a strong ability to solve complex problems and provide effective solutions.

• Strong communication and interpersonal skills, capable of working collaboratively in a dynamic team environment.

Additional Company Details

We do not accept any unsolicited resumes from external recruiting agencies or firms. The actual salary for this position will be determined by a number of factors, including the scope, complexity and location of the role; the skills, education, training, credentials and experience of the candidate; and other conditions of employment.

Sponsorship Details

Sponsorship not Offered for this Role Responsibilities The Data Engineer is responsible for designing, creating, deploying, and managing MEC's data architecture. The Data Engineer develops and maintains scalable data pipelines and build out new API integrations to support continuing increases in data volume and complexity. The role requires a deep understanding of analytics and database management to improve data reliability, efficiency, and quality. Key functions include but are not limited to: Design and Build Database Systems:

• Design, construct, install, test, and maintain highly scalable data management systems that meet both business requirements and industry best practices. Data Modeling and Design:

• Design data models and architecture patterns that consider functionality, cost, performance, scalability, reusability, security, and extensibility.

• Design conceptual, logical, and physical data models to support business intelligence and analytics.

• Architect data structures that eliminate redundancies and integrate disparate unstructured and structured data sources into coherent enterprise data models.

• Create detailed data structure representations such as Entity-Relationship Diagrams (ERDs). Data Strategy and Management:

• Develop and implement strategies for data acquisition, archival recovery, and database implementation, ensuring the optimization of data fidelity through cleansing and analysis.

• Perform data analysis, profiling, and validation to ensure accuracy and quality of data.

• Implement data governance and security measures to ensure data integrity and compliance with internal and regulatory standards. Integration and Migration: - Manage large datasets and maintain robust data from a wide array of source data systems (enterprise data warehouses, relational databases, APIs, document, unstructured data, big data, vector databases).

• Facilitate data migration from legacy systems to new solutions.

• Prepare data for prescriptive and predictive models. Performance Management: - Oversee and optimize data storage for all database systems and implement automated scripts for regular maintenance to enhance system performance. Collaboration and Support:

• Collaborate with data scientists, analysts, and other departmental leaders to address data-related technical needs and provide ongoing support and training.

• Actively participate in agile scrum ceremonies, including daily stand-ups, sprint planning, retrospectives, and reviews. Innovation and Research: - Stay updated with the latest industry trends and technologies in data architecture, data engineering, and data management.

• Identify strategic data/workflow gaps/opportunities and advocate for new technologies and techniques.