Java developer with Data Engineering

Core JAVA development including wrapper classes to support object-oriented features

Write Java classes, build JARs, perform unit testing, and optimize code for performance

Create entity models based on raw data sources

Build data pipelines for ingestion and incremental updates

Build automated test suites

Validate data quality and investigate data discrepancies

Review complex requirements and translate them into software designs and solutions

Write optimized code to clean, transform, and analyze large datasets

Knowledge sharing through peer programming, group code reviews

Adhere to code standardization and team best practices

Collaborate with team members, technical peers and stakeholders

Test data solutions, monitoring jobs, and fixing issues

Document technical specs and processes

Operate in various development environments (Agile, Kanban, Waterfall)

All other duties as assigned.

15+ years of Software Development experience

Design and implement models to transform complex, connected datasets into actionable business intelligence using graph analytics principles and technologies, Meticulous attention to details and strong problem-solving abilities

Ability to apply logic and critical thinking to interpret data patterns and connections between different data sources

Able to work with ambiguity, gaining clarity using independent analysis and thorough investigation

Ability to work with complex data models and data modeling principles

Understanding of relational database principles

High proficiency in core JAVA development language OOP, Collections, Multithreading, Data Structures and Exception Handling

Proficiency with JUNIT testing framework, Maven build tool, GitHub version control and IntelliJ IDE.

Proficient in Big Data Frameworks such as Apache Spark (preferred) or Hadoop

Knowledgeable in Azure Databricks, Delta Lake, Spark Core, Azure Data Factory (ADF) and Unity Catalog

Knowledgeable in analyzing data, finding data patterns, data visualization

Ability to ingest and transform data using PySpark in Azure Databricks

Understanding of key Data Warehousing and ETL/ELT Processes such as data pipelines and database management

Ability to design, build, and maintain robust Extract, Transform, Load (ETL) or Extract, Load, Transform (ELT) pipelines

Proficient in SQL and NoSQL databases, MySQL and Azure Cosmos DB are preferred

Knowledgeable in object-oriented programming (OOP) concepts, design patterns, and general software architecture

Knowledgeable in Cloud Platforms, such as Microsoft Azure (preferred) or AWS

Experience in performance optimization, including multi-threading, concurrency, and memory management

Ability to interpret complex data, visualize results, and explain insights to technical and non-technical stakeholders.

Ability to collaborate with internal and external technology resources.

Ability to write and review detailed technical specifications

Knowledge of software development methodologies (e.g., Scrum, Kanban, Waterfall)