Data Engineer

Data Engineer

Job Location: Houston, Texas

Job Type: Contract

Client: DISYS

Rate: Depend on Experience

Job Authorization: US Citizen/GC/EAD (H4/L2/TN) preferred C2C are open only for own Corp, not accepted from any employers

Responsibilities:

MINIMUM 8 YEARS DATA ENGINEERING EXPERIENCE PREFERRED

• Create and maintain optimal data pipeline architecture, assemble large, complex data sets that meet functional / non-functional business requirements.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS/big data technologies.
• Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
• Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
• Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
• Work with data and analytics experts to strive for greater functionality in our data systems.

Qualifications:

• Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
• Experience building and optimizing big data, data pipelines, architectures and data sets.
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
• Strong analytic skills related to working with unstructured datasets.
• Build processes supporting data transformation, data structures, metadata, dependency and workload management.
• A successful history of manipulating, processing and extracting value from large disconnected datasets.
• Working knowledge of message queuing, stream processing, and highly scalable big data, data stores.
• Strong project management and organizational skills.