Remote Principal Data Engineer

Summary

Join Nintex as a Principal Data Engineer and contribute to designing, developing, implementing, and mentoring on data engineering pipelines. As an expert in data acquisition and processing, you will ensure sufficient data history for data science modeling requirements, identify IP opportunities, and coordinate end-to-end pipelines.

Requirements

• 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

Responsibilities

• Ensure that data history is sufficient for data science modelling requirements
• Identify and forward Intellectual Property (IP) opportunities to the Nintex Patent process
• 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
• Create and maintain instrumentation that surfaces data ingestion systems’ stability and availability metrics
• 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.)
• Apply different data pipeline architectures appropriately to meet product requirements (data warehouse, data lake, data lakehouse, etc.)
• Identify and implement opportunities to optimize ETL processing to efficiently process large data sets
• Develop or adapt partitioning and data organization techniques for optimal querying of big data
• Implement data storage, access structures, and security protocols that meet Nintex’s data sovereignty and Personally Identifying Information (PII) policies
• Be an active part of the incident management process, including on-call rotation and being a key resource in the escalation response
• 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

Benefits

• 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