Java Data Reconciliation Engineer

5 days ago

Jersey City, New Jersey, United States Photon Full time
Job Title: Java Data Reconciliation Engineer

Summary:

We're seeking a skilled Java Data Reconciliation Engineer to drive the development of robust data reconciliation solutions within our financial systems. You will be responsible for designing, implementing, and maintaining Java-based applications to perform complex data reconciliations, identify and resolve discrepancies, and automate data matching processes.

Key Responsibilities:

Data Reconciliation Development:

Design, develop, and test Java-based applications to automate data reconciliation processes across various financial data sources, including relational databases, NoSQL databases, batch files, and real-time data streams.

Implement efficient data transformation, matching algorithm (deterministic and heuristic) with Java and relevant frameworks.

Develop robust error handling and exception management mechanisms to ensure data integrity and system resilience.

Data Analysis and Matching:

Collaborate with business analysts and data architects to understand data requirements and matching criteria.

Analyze and interpret data structures, formats, and relationships to implement effective data matching algorithms in Java.

Rules Engine Integration:

Integrate Java applications with rules engines (e.g., Drools) to implement and execute complex data matching rules.

Develop Java code to interact with the rules engine, manage rule execution, and handle rule-based decision-making.

Problem Solving and Gap Analysis:

Collaborate with cross-functional teams to identify and analyze data gaps and inconsistencies between systems.

Design and develop Java solutions to address data integration challenges and ensure data quality.

Contribute to the development of data governance and quality frameworks within the organization.

Qualifications and Skills:

A bachelor's degree in computer science or a related field.

9+ years of hands-on experience in Java development, preferably with exposure to data-intensive applications.

Strong understanding of data reconciliation principles, techniques, and best practices.

Proficiency in Java, Spring Data, and related technologies for data access and integration (e.g., Spring Data, Hibernate, JDBC).

Experience with rules engine integration and development (e.g., Drools).

Strong analytical and problem-solving skills, with the ability to translate business requirements into technical solutions.

Excellent communication and collaboration skills to work effectively with business analysts, data architects, and other team members.

Familiarity with data streaming platforms (e.g., Kafka, Kinesis) and data technologies (e.g., Hadoop, Spark) is a plus.

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