Job Category: Technology

Position Description

This person will be responsible for developing data pipelines, ensuring data quality and accuracy, and optimizing data transformation and collection for business intelligence reporting used by cross functional teams. The Business Intelligence Data Engineer will work collaboratively to develop and implement data models and data flows that act as the eyes and ears of a complex business spanning risk management, finance, and customer experience. Your efforts to assemble, transform, and share data will impact nearly all InterNex Capital’s operations and will be highly visible across the organization. The right candidate will be excited by the prospect of optimizing and re-designing the company’s data processes to support our next generation of products and data initiatives. The candidate will also have exposure and the opportunity to contribute to company projects utilizing the Google Cloud Platform.

Key traits for success in this position will be strong analytical, testing, project management, and communication skills, quick understanding of technical components, and direct & transparent collaboration towards solutions.

Additional Responsibilities

• Responsible for developing, testing, and maintaining InterNex Capital’s business intelligence platform.
• Optimize, debug, and maintain ETL jobs in an existing business intelligence tool (Domo) using data drawn from custom applications.
• Document ETL transformations from a business perspective.
• Manage data schemas and naming conventions across datasets to ensure consistency.
• Define testing procedures to validate changes to ETL have the desired and expected result in output datasets.
• Design, build, and maintain scalable data pipelines.
• Develop and deploy optimized data processing tasks.
• Build and maintain reports and dashboards using Domo.
• Develop and improve our CI/CD workflow tools and processes within Domo leveraging an integrated Sandbox environment.
• Contribute to the technical leadership of the team through documentation.

Required Qualifications

·         Bachelor’s degree in Computer Science or similar

·         Good knowledge of ETL processes and creating data pipelines, common data formats, regular expressions

·         Data Engineer with practical experience architecting, implementing, and managing SQL and NOSQL databases in physical, virtual and cloud environments.

·         Knowledge of SQL and Redshift to extract or manipulate data.

·         Experience writing reports with data stored in Oracle, Redshift and SQL Server databases.

·         Accustomed to working in an Agile development environment with external teams

·         Skilled in developing complex data ingestion and automated testing for data workflows

·         History of developing data models within lower environments and promoting to production

·         Expertise in parsing CSV, JSON, XML and similar file formats to cleanse/scrub data fields

·         Knowledge of Business Intelligence tools and experience with Domo is a significant advantage.

·         Experience with development best practices and toolchains.

Desired Qualifications

·         Start-up experience within a company and/or as an entrepreneur

·         Demonstrated applied technical knowledge in Git and Continuous Integration/Deployment tooling

·         Expertise in using Big Query or similar technologies.

·         Master’s degree in Computer Science

·         Comfortable communicating with non-technical team members