Senior Data Engineer

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.

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