Data Scientist (Big Data Engineer)

Overview

Remote
Depends on Experience
Accepts corp to corp applications
Contract - W2
Contract - Independent
Contract - 12 Month(s)

Skills

Algorithms
Amazon Web Services
Cloud Computing
Data Flow
Data Management
Data Modeling
Data Profiling
Data Quality
Data Science
Data Warehouse
Database
ERwin
Extract
Transform
Load
Extraction
IBM DB2
Informatica
Management
Microsoft SQL Server
Oracle
PL/SQL
RDBMS
Testing

Job Details

title : Data Scientist (Big Data Engineer)

Location : Austin , TX(Remote)

Job description

Minimum Requirements: Candidates that do not meet or exceed the minimum stated requirements (skills/experience) will not be considered for this opportunity.

Years ( leave no

blanks)

Years

Skills/Experience

Vendor Comments (as

applicable)

8

Design and develop Extraction, Transformation, Load (ETL) processes for enterprise data warehouse using Informatica; Deep hands-on expertise with Informatica ETL processes, development, data management, data profiling, data flows, data relationships, and data quality standards and processes

8

Hands-on experience with data warehouse development and testing (relational and dimensional) and proven evidence to implement using databases like Oracle, SQL Server etc. but preferably Oracle

8

Experience in Data Science

8

Hands on experience with data modeling preferably in a data warehouse environment

8

Experience with Informatica product suite in the Informatica cloud

8

Experience devising and utilizing algorithms and models to mine data; perform data and error analysis to improve models; clean and validate data for uniformity and accuracy

3

Experience with detecting and providing solutions to addressing mismatched data in case management systems

Preferred:

Years

Skills/Experience

Vendor Comment (as

applicable)

5

More than one type of RDBMS (DB2, SQL Server, Oracle)

5

Erwin or other equivalent data modeling tools

3

Experience in Amazon Web Services

2

Experience with detecting and providing solutions to addressing mismatched data in case management systems

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