Overview
Skills
Job Details
Location: Full-time on-site in Mclean, VA
We don't want visa dependent candidates
Assignment Type: CTH
Must Have Qualifications: Python, Pyspark, SQL. Understanding of Agile practices. Preferred Snowflake and Informatica.
Interview Information:
Rounds: 2 Rounds
Duration: 30 Minutes:60 Minutes
Interview Type: Virtual| In-Person
JOB DESCRIPTION:
The Senior Developer will be part of the client's Enterprise Risk Business Technology Office. This role will be responsible for supporting our organization s data-driven initiatives, specifically designing and building a data warehouse solution. This position requires strong experience in data analysis, modeling and engineering with the ability to translate complex technical issues into easily understood communications that will influence executive audiences with varied technical backgrounds and capabilities.
Qualifications:
Bachelor s degree in computer science, information technology or related field; advanced studies/degree preferred.
5 years extensive knowledge and experience in the Data technologies for Data Analytics, Data Lake/Mart/Warehouse, Databases SQL/NoSQL (DB2, Mongo, Postgres), Big Data Technologies (Spark or PySpark), ETL (Informatica, Talend), REST API, Integration/EAI technologies like Informatica
3+ years experience with Technologies including Web Service API, XML, JSON, JDBC, Java, Python.
3+ years working with SaaS platforms such as Snowflake, Collibra, Mongo/MongoDB Atlas,
Knowledge of enterprise data models, information classification, meta-data models, taxonomies and ontologies.
Exposure to Full stack enterprise application development(Agular, Spring Boot, Automation testing using Selenium)
5-7 years experience in a logical/physical data modeling, data architecture, data analysis, and data management role
Experience with different query languages such as PL/SQL, T-SQL, and ANSI SQL
Experience with database technologies such as DB2, PostgreSQL, Snowflake
Knowledge of data warehousing and business intelligence concepts including data mesh, data fabric, data lake, data warehouse, and data marts