Data Science Engineer (Journeyman)

Integral Federal•Annapolis Junction, MD

1d•Hybrid

About The Position

Integral Federal is looking to hire a Data Science Engineer to support a government customer as they continue to look for ways to enhance their layered approach to security through new state-of-the-art technologies, expanded use of existing and proven technologies, improved passenger identification techniques, and other developments that will continue to strengthen anti-terrorism capabilities.

Requirements

3+ years experience and a Bachelors Degree
Expertise developing interrogating databases with Structure Query Language (SQL) to develop complex queries involving joins, subqueries, aggregation, indices, common table expressions, and query optimization/plans. The ability to code and debug stored procedures is desirable.
Skills in applying pattern recognition techniques to large structured, semi-structured, and unstructured data sets to automate and optimize data wrangling (extract, transform, clean, evaluate, normalize/standardize, and organize) from disparate sources.
Previous experience as a data engineer or in a similar role
Technical expertise with data models, data mining, data cleansing, and segmentation techniques
Knowledge of programming languages (e.g. Java, Python, SQL). Skills with RHEL shell scripting
Hands-on experience with SQL
Great analytical skills
Previous experience with configuration management in data science and data analytics environments; also Microsoft Sharepoint and Agile project delivery and work management tools like JIRA or similar

Responsibilities

Analyze and organize raw data, build data systems and pipelines, and develop code/tools to Extract, Transform, and Load (ETL) data into the appropriate structures for storage
Combine raw information from different sources and explore ways to enhance data quality, performance, and reliability
Create performance metrics for data ingest, storage, and quality to track performance indicators for communication to relevant stakeholders.
Create and present consumable summaries of findings through effective communication and visualizations.
Perform data processing, cleansing, mining and analysis utilizing data sources having relevant context that are internal and external to the business’ domain data repositories/data warehouses.
Interpret, understand, and assess customer requirements to provide custom tool development, query optimization, aggregation, categorization, and interpretation of data.
Monitors for data quality events such as missing data, non-conformant data, and unexpected values and appropriately responds and resolves data quality issues
Capture data lineage and produce lineage reports to inform end users and customers how the data was sourced, transformed, and where it resides Extending data with third party sources of information when needed
Implement data governance practices and procedures that serve as the guides for data science projects
Support configuration management support of products and tools in data science and analytics environments