Sudsies, South Florida’s leading dry cleaning company, is seeking a skilled Data Engineer to join our growing and talented marketing team. We specialize in luxury and couture garment care. Believe us when we say there is nothing dry about the dry cleaning business!

In this role, you will be responsible for designing, building, and optimizing our data architecture and data pipelines. You will be responsible for transforming raw data into clean, structured datasets that power our analytics, reporting, and machine learning initiatives. You will work closely with Data Scientists, Analysts, and Software Engineers to ensure our data infrastructure is scalable, secure, and reliable.

More about Sudsies:

Our mission is to provide a human touch and user friendly systems in the delivery of our services. We invest our hearts, minds and humor into developing a bond with the human beings who are our customers and co-workers. We enjoy creating the warm, fuzzy, funny and unique experience that personifies the Sudsies brand for our customers. Our culture is all about taking ownership of everything in your world, from the good to your mistakes and shortfalls and not making excuses or blaming others. And then taking ownership of the solutions that will solve those problems. We even have our own Sudsies University!

In business for 30 years, Sudsies has grown to 5 stand alone boutiques in Dade, Broward, and Palm Beach counties. And we are growing nationwide. Many of our 200 employees have been long tenured. You will love working here!

Please visit www.sudsies.com to learn more about what we do!

More about the role:

Key responsibilities include:

Build Data Pipelines: Design, develop, and maintain automated ETL/ELT pipelines to ingest data from diverse sources (APIs, databases, logs, third-party tools).
Database & Warehouse Management: Optimize data storage systems and maintain data warehouses.
Data Modeling: Design robust data models, schemas, and architecture to support scalable data storage and efficient querying.
Optimize Performance: Troubleshoot data bottlenecks, optimize SQL queries, and ensure low-latency data access for analytics teams.
Ensure Data Quality: Implement data validation frameworks, monitoring systems, and data governance practices to guarantee data accuracy and compliance.
Infrastructure Management: Assist in provisioning and managing cloud-based data infrastructure using Infrastructure as Code (IaC) tools where applicable.

Skills/Experience required:

Education: Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related quantitative field or equivalent practical experience.
Programming Proficiency: Strong coding skills in Python, Scala, or Java.
Advanced SQL: Exceptional ability to write, debug, and optimize complex SQL queries.
Big Data & Pipelines: Hands-on experience with pipeline orchestration tools like Apache Airflow, Prefect, or Dagster, and stream/batch processing frameworks (e.g., Apache Spark).
Cloud Architecture: Experience building data solutions on cloud platforms like AWS, Azure, or Google Cloud (GCP**)**.
Version Control & CI/CD: Proficiency with Git and continuous integration/continuous deployment pipelines.

Pay: $67,000.00 - $114,000.00 per year

Benefits:

Dental insurance
Health insurance
Paid time off
Vision insurance

Application Question(s):

This role will require you to work on Saturdays, especially during the initial 90 day ramp up period. Are you able to work on Saturdays?
This role is on site. Are you able to work on site?

Experience:

data engineer: 2 years (Preferred)

Work Location: In person

Job description