Java Integration Engineer

Responsibilities & Essential Functions
This role will be driving larger more complicated projects independently as well as mentoring less experienced engineers. Data Engineer will collaborate with business partners and cross-functional teams on data/reporting
requests. The assignments will become broader in nature, usually requiring originality and ingenuity. This role will be accountable for successful outcomes related to designing, developing, implementing, optimizing, and maintaining data integrations, pipelines and solutions.

Skills, Experience, and Qualifications
Skills:
- Mandatory: Java, JDBC Template, JPA, Springboot, Ehache, SQL, REST.
- Proficiency in the following languages: Java, SQL, Python and Scala (prioritized order)
- Data Modeling: Creation of conceptual, logical, and physical data models for data objects, object attributes, and their relationships
- Analytical Skills: Data Engineers work with large amounts of data that will include facts, figures, and number crunching. You will need to profile the data and analyze it to find conclusions.
- Communication Skills: Data engineers are often called to present their findings or translate the data into an understandable document. You will need to write and speak clearly, easily communicating complex ideas.
- Critical Thinking: Data engineers must look at the numbers, trends, and data and come to new conclusions based on the findings.
- Attention to Detail: Data is precise. Data engineers must make sure they are vigilant in their analysis to come to correct conclusions.
- Math Skills: Data engineers need advanced math skills to estimate numerical data. Insurance experience required as well as insurance products.
- Debugging Skills: Data engineers need the ability to analyze issues with components in our data solutions and come up with remediation plans.

Experience:
- Experience in Java development with Java 8 & above, J2EE, , Hibernate, Maven, GiT, Jenkins, JSON frameworks, XML, JMS, JDBC, Junit based testing frameworks like Mockito
- Demonstrated proficiency in Spring Framework including Data (JDBC, ORM, JMS), Security & Integration
- Proven experience in data engineering, implementation of best practices for data storage, integration, transformation, access, etc., within Azure and on-premise platforms
- Experience in building and optimizing real-time and near real time data integration solutions for scale, performance, reliability, and cost efficiency
- Experience with event streaming solutions like Apache Kafka and /or near real time messaging
solutions such as Azure Service Bus is preferred.
- Experience in optimizing data pipelines to account for scale, performance, reliability, and cost efficiency is preferred
- Demonstrated proficiency in relational, NoSQL, hierarchical, and entity relationship data modeling
- Experience in creating easy to consume documentation of data processes and solutions to aid in knowledge transfer and continuity.
- Experienced in agile development methodologies, developing high quality code, and DevOps best practices
- Strong foundations with core Java concepts. Good understanding of Aspect Oriented Programming (AOP), Test Driven Development (TDD)
- Solid grasp of HTTP, RESTful webservices, Linux operating systems
- Coaching and mentoring less senior team member as well as conducting reviews for their work

Qualifications:
- Bachelor's degree or higher in Data Science, Mathematics, Statistics, Computer Science, Information Systems, Business Information Technology, or equivalent
- Professional experience in data engineering, data architecture, data integration
- Professional experience in Java development and Spring Framework
- PREFERRED: Holds active Azure DP-203 (Microsoft Certified: Azure Data Engineer Associate) or equivalent. Other Azure DP certifications or equivalents are also applicable