Data Engineer

Summary

Join Nintex as a Data Engineer and contribute to the development of high-quality data engineering products and services. You will be part of a team building a new Data Platform using the latest cloud technologies. This is a one-year contract role requiring active participation in agile development, data engineering design and development, and collaboration with stakeholders. You will ensure data quality, create data models, and optimize data processes. The role also involves incident management and working with data providers to document data streams.

Requirements

• 3+ years experience in data engineering
• Bachelor’s degree in computer science
• Cloud Platform, i.e. AWS / Azure / GCP
• Cloud DBMS, i.e. Databricks / Snowflake / Amazon Redshift / BigQuery
• Distributed Data frameworks, i.e. Hadoop / Spark / Flink
• Programming, i.e. Java / Scala / Python
• SQL, any variant is a good foundation but HiveQL / Spark SQL preferred
• Source Control, i.e. Git
• Database modeling, i.e. Snowflake Schema / Star Schema / Data Vault

Responsibilities

• Participate actively in agile development cycle meetings
• Design, code, and unit test data engineering components and features that can be released / deployed through automation
• Ensure data completeness and correctness through cross-referencing to original data source
• Design and develop ETL’s in line with best practices and techniques for data transformation and storage
• Deliver data engineering functions that ingest, sanitize, and join data from multiple sources
• Create data models that meet the needs of management stakeholders, data scientists, and analysts as required
• Analyze and evaluate data product/output to identify and recommend optimizations as required in its extraction, cleansing, and organization
• Identify and pursue opportunities to create or improve organizational data standards
• Take ownership of assigned work and liaise proactively and collaboratively with stakeholders to ensure quality features are produced on time
• Participate in technical and team interviews as directed and provide clear input into the decision-making process
• Proactively communicate your work and progress to your manager, extended technical team, and stakeholders during the development process, and immediately escalate any product quality or delivery issues
• Contribute to the support and maintenance of data engineering functions, including liaising with the support team to resolve issues that have been escalated
• Be an active part of the incident management process, including on-call rotation and working with the IM team to resolve incidents
• Work with data providers to document the incoming data stream’s domain boundaries, field datatypes, and term definitions in sufficient detail to enable transformation of the data for end-user consumption
• Design and implement data engineering solutions that adhere to Nintex guidelines in support of security, disaster recovery, scalability, availability, reliability, and durability

Preferred Qualifications

• Streaming and event-driven systems, i.e. Apache Kafka / Azure EventHubs / Spark Structured Streaming
• Data testing, i.e. unit tests and quality enforcement
• DevOps platform, i.e. Azure DevOps / GitHub
• Scripting, i.e. bash / Powershell
• Infrastructure as code, i.e. Terraform / ARM templates / AWS Cloudformation

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
• Multiple tools through which to learn and grow, and an incredible global community
• 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