Who we are
Cooperative Computing (C|C) is a digital enablement organization enabling organizations to effectively operate in the automated economy. The future of business is in maximizing relationships through the effective use of technology. With our clients, we discover, strategically engineer a digital strategy and enable these strategies through the implementation of best-in-class applications to achieve clients 10x growth.
Our performance culture is built through our team members, working together to help our clients succeed. We inspire growth with our team members in delivering fanatical and passionate client experiences, knowing effective technology is built with and for people.
About the Role:
The Data Engineer position at our company entails joining a dedicated team of analytics professionals. The role is primarily focused on broadening and enhancing our data and data pipeline architecture while streamlining data flow and collection for multiple functional teams. The successful candidate will play a vital role in creating an environment that supports optimal data extraction, transformation, and loading from diverse data sources.
Mission:
The Data Engineer's mission is to ensure an optimal data pipeline architecture and gather complex data sets that meet the business's functional and non-functional requirements. Their goal is to identify, design, and implement internal process improvements, automate manual processes, enhance data delivery, and re-architect infrastructure for greater scalability.
Capabilities (Key Behaviors):
The Data Engineer will exhibit the following capabilities:
Bachelor's degree in data science, computer science, or a related field.
Must be able to work 9 am to 6 pm Central Standard Time Zone.
Technical expertise in data models, data mining, and segmentation techniques.
2+ years of experience in a programming language, preferably Python.
8+ years of experience with advanced SQL/MySQL/Snowflake/PostgreSQL database design and T-SQL.
6+ years of experience in Business Intelligence and data visualization tools such as Tableau, Microsoft Power BI, or Looker.
Advanced working knowledge of SQL/MySQL/Snowflake/PostgreSQL and experience with relational databases and query authoring.
Passion for data analytics and fast learning ability.
Strong communication skills for client meetings.
Experience in Machine Learning is a big plus.
Ability to work independently, solve problems, and learn quickly as part of an agile team.
Create and maintain efficient data pipeline architectures that support data processing and analysis.
Assemble large, complex data sets that meet both functional and non-functional business requirements.
Identify and implement process improvements, automate manual processes, and optimize data delivery.
Build infrastructure for optimal data extraction, transformation, and loading from diverse data sources using Advanced SQL and AWS 'big data' technologies.
Develop analytics tools that leverage data pipelines to provide actionable insights into customer acquisition, operational efficiency, and key business performance metrics.
Collaborate with cross-functional teams including Executive, Product, Data, and Design to address data-related technical issues and support data infrastructure needs.
Results:
Design and maintain data pipelines that ensure smooth data processing and analysis.
Assemble high-quality, comprehensive data sets to meet diverse business requirements.
Drive internal process improvements, automation, and data delivery optimization.
Build robust infrastructure for data extraction, transformation, and loading from a variety of data sources.
Develop analytics tools that enable data-driven decision-making and provide valuable insights.
Assist cross-functional teams with data-related technical challenges and support data infrastructure needs.
Apply advanced database design techniques to ensure efficient and scalable data storage.
Utilize Business Intelligence tools to create meaningful data visualizations for stakeholders.
Enable teams to make informed decisions through access to accurate and actionable data.
Address data-related challenges and technical issues in a timely and effective manner.
Optimize data query performance for relational databases using SQL.
Stay up to date with emerging data engineering technologies and techniques.
Provide reliable data engineering support, ensuring data availability and accuracy.
Collaborate effectively with colleagues to drive agile development and project success.
Contribute to the generation of valuable insights that drive business growth and improvement.