Sr Java Developer
Top Skills' Details
1. Extensive experience working with Java applications on both the front end and back end - will have a UI focus with - Angular, Typescript, JavaScript
2. Strong data lake experience - consume data, ingest data, hydrate date into the data lake, bring data into a UI reporting dashboard to showcase risk metrics.
- strong perspective on data lake principals and data science
3. Strong AWS experience
4. NodeJS - heavy UI knowledge within JavaScript and Angular
5.. This is a senior level candidate with great communication, ability to reverse engineer and understand architectural principals.
Background with Mortgaged backed securities, fixed income models, risk models, securities, hedges etc. is extremely helpful for this group.
Job Description
Backend Development
NodeJS, Java, Python, SpringBoot,
Familiar with Tools: Intellij, VSCode, DBeaver, Postman, Putty
Frontend Development
Angular - NgRx, RxJS, TypeScript, JavaScript
Databases
DynamoDB, Postgres, Oracle
Write and optimize SQL
AWS services
Lambda, S3, Step Functions, Glue, EC2, ECS, CloudFormation, RDS, CloudWatch, Redshift, REST API, AWS CLI
Development Testing
Unit test & Automation : Junit, Mockito, Selenium, Cucumber
DevOps
Docker, Git, Jenkins, GitLab,
Excellent communication skills
Data ingestion:
Ability to design and implement pipelines to extract data from different sources (databases, APIs, applications, etc.) and load it into the data lake in a raw format.
Data storage management:
Understanding of data lake storage options (like cloud object storage services) and how to organize data efficiently within the lake, including partitioning and data lifecycle management.
Data processing:
Proficiency in using distributed processing frameworks (like Apache Spark) to transform and clean raw data within the data lake, including data cleaning, aggregation, and feature engineering.
Data querying and analysis:
Familiarity with tools and languages (like HiveQL, Presto, or Python with libraries like Pandas) to query the data stored in the data lake for analysis and reporting.
Data governance and security:
Knowledge of data governance practices to ensure data quality, access control, and compliance within the data lake environment.
Common data lake technologies a developer might use:
Cloud platforms: AWS S3, Azure Data Lake Storage, Google Cloud Storage