Data Engineering and JAVA experience
Remote
W2 only
Design and implement models to transform complex, connected datasets into actionable business intelligence using graph analytics principles and technologies
- 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.
Skills:
- 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)