Data Engineer I

For over four decades, PAR Technology Corporation (NYSE: PAR) has been a leader in restaurant technology, empowering brands worldwide to create lasting connections with their guests. Our innovative solutions and commitment to excellence provide comprehensive software and hardware that enable seamless experiences and drive growth for over 100,000 restaurants in more than 110 countries. Embracing our "Better Together" ethos, we offer Unified Customer Experience solutions, combining point-of-sale, digital ordering, loyalty and back-office software solutions as well as industry-leading hardware and drive-thru offerings. To learn more, visit partech.com or connect with us on LinkedIn, X (formerly Twitter), Facebook, and Instagram.

We are looking for a Data Engineer that will play a critical role in shaping our data innovations. They will help create cutting-edge Big Data solutions by leveraging their prior industrial experience. This role requires close collaboration with the Machine Learning, Software Engineering, and Product Departments where you will be given the opportunity to not only serve internal teams, but also our business clients.

Remote, Markham, CA

Remote, Toronto, CA

Data Engineering Manager

Requirements:

• 3+ years of experience as a Data engineering professional, developing scalable big data solutions

• Degree in Computer Science, Engineering, or other related fields

• Demonstrated strength in data modelling and SQL within a Lakehouse architecture

• Knowledge of cloud technologies, preferably AWS

• Knowledge of big data technologies and programming language (Python), relational databases (Postgres, MySQL), NoSQL (MongoDB), and streaming (Kafka, Spark)

• Must have PySpark and Spark Streaming experience

• Must have Databricks experience

Additional skills:

• Excellent software engineering background with high familiarity with the software development lifecycle

• Familiarity with GitHub and version control best practices

• Strong problem-solving skills with demonstrated rigor in building and maintaining a complex data pipeline

• Good communication skills and ability to articulate complex concepts with thoughtful, actionable recommendations

• Work with large data sets and implement sophisticated data pipelines with both structured and semi-structured data

• Collaborate with stakeholders to design scalable solutions

• Manage and optimize our internal data pipeline that supports marketing, customer success and data science

• Focus on ingesting, storing, processing, and analyzing large datasets

• Be a technical contributor to PAR’s big data platform that supports AI and BI products

• Work with infra and operations teams to monitor and optimize existing infrastructure

• Develop and implement pipelines that extract, transform, and load data into information products that help the organization reach its strategic goals

• Help define data governance policies and support data-versioning processes

• Occasional business trips are required

• Leverage AI tools to streamline data pipeline development, accelerate root-cause analysis, and automate routine data quality checks to improve engineering efficiency 

• Interview #1: Phone Screen with Talent Acquisition Team

• Interview #2: Video interview with the Hiring Manager (via MS Teams)

• Interview #3: Video interview (technical) with the Team (via MS Teams)

• Interview #4: Video interview (technical) with the Team (via MS Teams)

PAR is proud to provide equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability or genetics. We also provide reasonable accommodations to individuals with disabilities in accordance with applicable laws. If you require reasonable accommodation to complete a job application, pre-employment testing, a job interview or to otherwise participate in the hiring process, or for your role at PAR, please contact accommodations@partech.com. If you’d like more information about your EEO rights as an applicant, please visit the US Department of Labor's website.