Senior Data Engineer

PAR Technology

$100K — $130K *
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years of experience in Senior Data Engineering, focusing on scalable big data solutions
  • Advanced degree in Computer Science, Engineering, or related fields
  • Strong data modelling and SQL skills within Lakehouse architecture
  • Extensive knowledge of cloud technologies (AWS, Azure)
  • Advanced proficiency in big data technologies, Python, Java, relational databases, NoSQL, and streaming technologies
  • Experience with PySpark and Spark Streaming is essential
  • Practical experience with Databricks is required

Responsibilities

  • Implement sophisticated data pipelines for large datasets including structured and semi-structured data
  • Collaborate with stakeholders to design scalable data solutions
  • Manage and optimize internal data pipelines for marketing, customer success, and data science
  • Focus on ingesting, storing, processing, and analyzing large datasets
  • Lead technical initiatives for the big data platform supporting AI and BI products
  • Collaborate with operations teams to monitor and optimize infrastructure
  • Develop and implement ETL pipelines that contribute to strategic organizational goals
  • Define data governance policies and support data versioning processes
  • Leverage AI tools to enhance data pipeline efficiency and automate reporting

Benefits

  • Flexible remote work options from Markham or Toronto, CA
  • Opportunity to collaborate closely with diverse internal teams and business clients
  • Engagement in cutting-edge big data solutions and AI technologies
  • Professional development through technical leadership and innovative projects
  • Occasional business trips to foster collaboration and networking opportunities
Full Job Description
Position Description:

We are looking for a Senior 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.

Position Location:

Remote, Markham, CA

Remote, Toronto, CA

Reports To:

Data Engineering Manager

What We're Looking For:

Requirements:
  • 5+ years of experience as a Sr Data engineering professional, developing scalable big data solutions
  • Advanced degree in Computer Science, Engineering, or other related fields
  • Demonstrated strength in data modelling and SQL within a Lakehouse architecture
  • Extensive knowledge of cloud technologies, e.g. AWS and Azure
  • Advanced knowledge of big data technologies and programming languages (Python, Java), 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 complex data pipelines
  • Exceptional communication skills and ability to articulate complex concepts with thoughtful, actionable recommendations


Unleash your potential: What you will be doing and owning:
  • 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 leader of 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, generate data insights, and automate reporting to accelerate engineering productivity and decision-making

Interview Process:
  • 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)

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