Sr. Data Engineer

Overview

As our Sr. Data Engineer, you’ll help drive Concora Credit’s Mission to enable customers to Do More with Credit – every single day.

 

The impact you’ll have at Concora Credit:

As a Sr. Data Engineer, your primary role will be to design and own the data models that support reporting and analysis across the organization - dimensional schemas, foundational data marts, and key data structures.

These models are informed by data-driven analysis of business performance and improvement opportunities. You will also build the engineering around those models: data pipeline architecture, data flows, data transformations, and clear documentation.

You'll join our Analytics Engineering team and partner with data owners and users to build, problem-solve, and optimize the data structures other teams rely on.

We hire people, not positions. That's because, at Concora Credit, we put people first, including our customers, partners, and Team Members. Concora Credit is guided by a single purpose: to help non-prime customers do more with credit. Today, we have helped millions of customers access credit. Our industry leadership, resilience, and willingness to adapt ensure we can help our partners responsibly say yes to millions more. As a company grounded in entrepreneurship, we're looking to expand our team and are looking for people who foster innovation, strive to make an impact, and want to Do More! We’re an established company with over 20 years of experience, but now we’re taking things to the next level. We're seeking someone who wants to impact the business and play a pivotal role in leading the charge for change.

Responsibilities

As our Sr. Data Engineer, you will:

• Design and maintain foundational data marts and dimensional data models (star and snowflake schemas, fact and dimension tables) and that serve as a durable, reusable foundation for analytics and management reporting.
• Define data grain, key structures, and slowly changing dimension (SCD) strategies so data marts stay accurate and reliable as the underlying business changes.
• Create and manage large, complex data sets that meet business requirements and inform critical decision-making across the organization.
• Create and maintain optimal data pipeline architecture, including optimal extraction, transformation, and loading of data, leveraging Databricks notebooks, Apache Spark (SQL, Python), and other Microsoft Azure or open-source tools as required.
• Document data models, transformation logic, and data lineage clearly enough that analysts and engineers outside the team can understand and trust the data without relying on the original author.
• Analyze business performance, identify improvement opportunities, deliver recommendations, and manage implementation.
• Perform all duties and responsibilities, leveraging strong quantitative, critical thinking, and communication skills.
• Effectively communicate analytical approaches, relevant findings, and recommendations with supporting evidence throughout the organization.
• Perform ad-hoc queries to support analysis.
• Work with stakeholders to interpret, research, and resolve data-related technical issues and support their data infrastructure needs.

 

These duties must be performed with or without reasonable accommodation.

 

We know experience comes in many forms and that many skills are transferable. If your experience is close to what we're looking for, consider applying. Diversity has made us the entrepreneurial and innovative company that we are today.

Qualifications

Requirements:

• 3 to 5 years of experience in data engineering, with a strong focus on dimensional data modeling and building data marts or warehouses for analytics.
• Demonstrated ability to design data structures for reuse and longevity (correct grain, key design, slowly changing dimensions), not just to answer a single reporting request.
• Collaborate with analysts, data scientists, and business stakeholders in Risk, Operations and Finance to understand data needs and deliver reliable, reusable datasets
• Strong ability to write and optimize complex SQL queries.
• Design and develop scalable, efficient data pipelines using Azure Databricks
• Fluent with Python scripting.
• Optimize performance and cost efficiency across large-scale distributed data systems
• Monitor, troubleshoot, and optimize existing pipelines and infrastructure to ensure reliability and scalability
• Excellent problem solver, disciplined attention to detail, great communicator.
• Strong quantitative skills and communication skills – verbal and written.
• Self-starter