Hiring Data Engineer in Louisville

CodeHire Global Solutions INC is a U.S.-based IT consulting firm with 12 years of experience building custom, scalable data infrastructure for mid-market clients in manufacturing, logistics and healthcare across North America. We specialize in bridging legacy on-premises systems with modern cloud data stacks, helping our clients unlock actionable insights from their operational data to drive efficiency and revenue growth. Our team of 42 data and technology professionals operates out of our downtown Louisville, KY office, with a hybrid work model designed to balance in-person collaboration with flexible independent work.

We are currently hiring a full-time Data Engineer to join our growing data practice, based in our Louisville office with a hybrid schedule requiring 3 days of on-site work per week. Relocation to the Louisville area is accepted for qualified out-of-area candidates, and we offer a $5,000 relocation stipend to support moving costs for new hires who need to relocate for this role. This position is ideal for a data engineer with 5 to 7 years of professional experience building and maintaining production data pipelines for enterprise use cases, who is comfortable working directly with clients to deliver tailored data solutions.

In this role, you will own end-to-end development and maintenance of data pipelines and infrastructure for 4 active enterprise clients, with responsibilities including:
1. Design, build and maintain 15+ production ETL/ELT pipelines using Apache Spark, AWS Glue and dbt, processing 2TB+ of structured and unstructured data daily, with 99.95% uptime and a <15 minute SLA for critical pipeline failures.
2. Optimize MongoDB and PostgreSQL database performance for client analytics use cases, reducing query latency by 30% for 12 core business intelligence reports across supply chain and patient intake datasets.
3. Implement and manage real-time data streaming workflows with Apache Kafka and AWS Kinesis, supporting near real-time inventory tracking and patient wait time monitoring for 3 core client use cases.
4. Develop and enforce data governance standards, including data lineage documentation, access control policies and data quality validation rules, reducing invalid data entries by 25% across client data warehouses.
5. Collaborate with cross-functional teams of data scientists, business analysts and client stakeholders to translate business requirements into scalable data architecture solutions, delivering 4+ client data projects per year on budget and on timeline.
6. Maintain and optimize Snowflake cloud data warehouse environments, including cost allocation tracking and storage tiering, reducing annual client cloud data spend by 18% on average.
7. Build and maintain CI/CD pipelines for data workflows using GitHub Actions and Jenkins, automating testing and deployment of pipeline updates, cutting release cycle time from 2 weeks to 3 days.
8. Troubleshoot and resolve production data incidents within SLA targets, conducting root cause analysis and implementing preventive measures to reduce recurring pipeline failures by 40% year over year.

Our Louisville office is located in the downtown tech corridor, with a collaborative open workspace plus quiet focus rooms for deep, uninterrupted work. We operate a hybrid model that prioritizes in-person collaboration for sprint planning, client workshops and team problem-solving, while allowing flexible remote work for individual task execution. Our team operates with a flat hierarchy that encourages open feedback and knowledge sharing, and we host monthly data deep dive sessions where team members share lessons learned from recent projects to improve our collective practice. We cover 100% of costs for professional conference attendance and relevant technical certifications for all employees, and offer a flexible PTO policy with no differentiation between sick leave and vacation time, providing a minimum of 3 weeks of paid time off per year for all full-time staff, plus 10 paid company holidays.

To qualify for this role, you must have 5 to 7 years of professional experience in data engineering or a related data-focused role, with a track record of delivering production data pipelines for enterprise clients. Hands-on experience with MongoDB, ETL/ELT development, and at least one major cloud platform (AWS preferred, as we primarily use AWS for client deployments) is required. Strong proficiency in SQL and at least one programming language commonly used for data work (Python preferred, Scala or Java also acceptable) is mandatory. Experience with data streaming tools (Kafka, Kinesis, AWS MSK) and cloud data warehouses (Snowflake, Redshift, BigQuery) is required. Familiarity with data governance frameworks, data quality tools (Great Expectations, dbt tests) and CI/CD practices for data workflows is a strong plus. You must be able to clear a standard background check, as we work with healthcare and logistics clients with strict data security requirements.

We offer a competitive total compensation package for this role, including a base salary ranging from $105,000 to $135,000 per year, depending on your experience and technical skill set, plus a performance-based annual bonus of up to 15% of your base salary. Full benefits include 100% employer-paid health, dental and vision insurance for you and your dependents, a 401(k) plan with 4% employer match, and a $2,000 annual professional development stipend that can be used for certifications, courses, conference attendance or technical books. We also offer flexible working hours within core collaboration hours of 10am to 3pm ET, to accommodate different working styles and personal commitments.

This role includes clear opportunities for career growth: we have a structured progression framework for data engineers, with paths to advance to Senior Data Engineer, Lead Data Engineer or Data Architect roles within 2 to 3 years of consistent high performance. We also support internal mobility to client-facing data consulting roles or internal product development roles if you are interested in shifting your career focus. Our bi-annual performance reviews use clear, measurable goals tied to promotion and bonus eligibility, so you will always have transparency around what is required to advance your career with us.

The hiring process for this role consists of 4 steps, with an expected timeline of 3 weeks from application receipt to offer. First, we will review your application and reach out within 2 business days if your experience aligns with the role requirements. Next, you will complete a 60-minute technical screening call with our lead data engineering manager, where you will discuss your past project experience and complete a short, practical coding exercise related to ETL pipeline development. If you pass the screening, you will be invited to a 2-hour virtual panel interview with 2 members of our data engineering team and 1 client success manager, where you will walk through a past data project you led and discuss how you would approach a hypothetical client use case. The final step is a 30-minute call with our VP of Engineering to discuss team fit and career goals. If you are selected for the role, we will extend a formal offer within 1 business day of the final interview, with a start date flexible to your availability, typically within 2 to 4 weeks of offer acceptance. To apply, send your resume and a brief summary of your relevant data engineering project experience to [email protected].