Nintex

Principal Data Engineer

Johannesburg, South Africa
Unity Azure Hadoop Spark Kafka Scala Python Streaming
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Description

About Nintex:  

At Nintex, we are transforming the way people work, everywhere.   

As the global standard for process intelligence and automation, we're trusted by over 10,000 public and private sector organizations across 90 countries. Our customers, from industry giants like Amazon, Coca-Cola, and Microsoft, rely on the Nintex Platform to accelerate their digital transformation journeys by managing, automating, and optimizing business processes quickly and efficiently. We improve their lives through the technology we build.  

We are committed to fostering a workplace that supports amazing people in doing their very best work every day. Collaboration is constant, our workplace is fun, the environment is fast-paced, and we value our people’s curiosity, ideas, and enthusiasm. Driven by passion and accountability, we take initiative, measure progress, and deliver results. Our culture fosters innovation and problem-solving, fueled by curiosity and a commitment to thinking big. Together, we move with agility, prioritize customer needs, and build unity through empathy, leaving a positive impact wherever we go.  

Working in engineering:

Working at Nintex as an engineer means building more than just software; it’s about making a tangible impact with every line of code. Our engineers are process experts, developing the industry’s most complete process and automation platform to transform the way people work. If you’re interested, curious and want to learn and do more, the sky is the limit here. We take a solutions-oriented and collaborative approach, constantly innovating our business and products. 

About the role: 

You are an expert in data acquisition and processing not only in your team’s domain, but also across Nintex. Your technical leadership demonstrates a passion for quality data engineering and is demonstrated across multiple, complex projects and in assistance to other teams. You mentor other engineers and provide experienced advice in your specialties across other teams. You look for opportunities to mine data from development and operations that usefully informs development and product decisions. Your data engineering pipelines are designed with the possible downstream requirements of data analysts and scientists in mind. 

As a Principal Data Engineer, you are focused on the work of your team and domain, but you also have a larger role across Nintex and in the outside data engineering community. You will participate in larger projects on occasion, but your focus is designing, developing, implementing and mentoring on your team’s assigned deliverables. 

Your contribution will be:  

  • You ensure that data history is sufficient for data science modelling requirements.
  • You identify and forward Intellectual Property (IP) opportunities to the Nintex Patent process.
  • You coordinate the data inputs from multiple sources to fashion an end-to-end pipeline to create report artifacts that meet all reporting objectives of management stakeholders.
  • You create and maintain instrumentation that surfaces data ingestion systems’ stability and availability metrics.
  • You use Azure event hubs and functions to implement required data operations while leveraging Azure product strengths and compensating for its limitations (scaling, error handling, and etc.).
  • You apply different data pipeline architectures appropriately to meet product requirements (data warehouse, data lake, data lakehouse, etc.).
  • You identify and implement opportunities to optimize ETL processing to efficiently process large data sets.
  • You develop or adapt partitioning and data organization techniques for optimal querying of big data.
  • You implement data storage, access structures, and security protocols that meet Nintex’s data sovereignty and Personally Identifying Information (PII) policies.
  • You are an active part of the incident management process, including on-call rotation and being a key resource in the escalation response.
  • You work with data providers to document the incoming data stream’s domain boundaries, datatypes, and term definitions in sufficient detail to enable transformation of the data for end-user consumption. 

To be successful, we think you need:  

  • You have 8+ years experience in data engineering
  • Hands-on experience with PaaS
  • Experience with DataBricks, Azure, Unity Catalog
  • Experience with Hadoop/Spark, Kafka and Azure OpenAI
  • Experience with Scala and Python is advantageous
  • Experience with real-time data streaming and any distributed computing experience would be advantageous

What’s in it for you? 

Our people work in the way that best suits them and their teams - whether at home, in an office, or another place that sparks creativity, focus, and collaboration. Our work environment is such that our people can successfully deliver their work while adequately supporting their lifestyle and preferences. 

While our offerings differ from country to country, we offer our entire global workforce an array of exciting perks and benefits, including 

  • Global Gratitude and Recharge Days
  • Flexible, paid time off policy
  • Employee wellness programs and counseling resources
  • Meaningful peer recognition and awards
  • Paid parental leave
  • Invention/patenting assistance
  • Community impact, paid volunteer time, and opportunities
  • Intercultural learning and celebration
  • Multiple tools through which to learn and grow, and an incredible global community 

View more about our benefits here: https://www.nintex.com/wp-content/uploads/2023/01/Global-Perks-and-Benefits.pdf 

Equity Statement: Preference will be given to People Living with Disability who are members of the designated groups in line with the Employment Equity Plan and Targets of the Company.

#LI-REMOTE

Nintex
Nintex
Analytics Business Intelligence Business Process Automation (BPA) Computer Vision Enterprise Software Machine Learning Robotic Process Automation (RPA) Robotics Software Virtual Workforce

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