Data Engineer

Data Engineer Company: Boeing Vancouver Boeing Vancouver is seeking a Data Engineer , reporting to the Manager of Data Science & Analytics working out of the Richmond, BC office. This role will help Boeing transform our industry through the application and continuous improvement of advanced analytics and machine learning in the aviation domain. The position will be embedded in a multi-disciplinary data science team producing industry-leading insights, and will use their data management, software development and infrastructure skills to help build bigger, faster, and better cloud-based tools and pipelines. They will be broadly responsible for the design, implementation and support of data pipelines, including the data models, data contracts, and model features. This is a challenging role, requiring versatile problem-solver with keen conceptual mind, ontological thinking, an understanding of data science and valuable data features, as well as computational load and performance. They will work closely with aviation engineers and data scientists in a problem-solving role, helping bridge the gap from data into working data science models and applications. Although primarily responsible for data management, the Data Engineer must be a versatile team player and may be called upon to assist in back-end development, cloud deployment, and even data science from time to time. They must be able to adapt, find the knowledge they need, learn, and make decisions as needs arise. Position Responsibilities : Leads cross-functional teams to determine, define and deploy complex predictive/prescriptive analytic solutions to meet business objectives. Evaluates business objectives and determines stakeholder needs. Chooses best fit methods, defines algorithms, validates and deploys models to achieve business results. Performs necessary data preparation and enhancements to models. Support team data science modeling, analytical applications, and problem-solving efforts. Propose data engineering solutions to support different modeling strategies. Design, build and support healthy, automated, and repeatable data ingestion and processing pipelines: Raw data ingestion, cleansing, and data contracts. Design data models and data contracts. Monitor and maintain data quality, integrity, consistency. Help design and build scalable, reliable, and high-performance systems and environments. Effectively contribute to building the overall knowledge and expertise of the technical team. Participate in work and code reviews with the team. Take part in implementation and support of continuous integration and continuous delivery (CI/CD). Work on systems to monitor system health, data quality and scientific performance. Implement data access-control for compliance with data governance policies. Contribute to technical documentation. Collaborate with developers, data analysts, data scientists and organizational leaders to identify opportunities for process improvements. Exhibit sound judgment, keen eye for details and tenacity for solving difficult problems. This position is hybrid. This means that the selected candidate will be required to perform some work onsite at Richmond location. This is at the hiring team’s discretion and could potentially change in the future. Employer will not sponsor applicants for employment visa status. Basic Qualifications (Required Skills/Experience): Minimum 4-years’ Cloud deployment experience (Azure preferred). Minimum 4 years’ experience in relational and non-relational database technologies. Minimum 4-years’ experience supporting data science and analytics projects and/or infrastructure. Must be proficient in Python. Provide consent to Canadian Government Controlled Goods Program (CGP) assessment and willing and eligible to work on government and defense-related programs. Must be legally able to work in Canada. Individuals must not pose a risk for safeguarding of controlled goods. Must be eligible to handle US export-controlled data. Preferred Qualifications (Education/Experience): Experience working with Databricks. A technical degree/diploma in a related field of study. Experience working with Large Language Models (LLM) and Natural Language Processing (NLP) technologies. Experience working with graph databases, knowledge graphs, and their languages (e.g. GraphQL, Cypher). Experience designing and implementing data quality monitoring solutions. Expertise in data modeling principles/methods. Experience with development, deployment and version control tools. Experience with production-level Software Development. Experience in DevOps technologies (e.g. CI/CD, Docker) and practices. Experience with cloud-deployed APIs and micro-services is an asset. Experience in pipeline software is an asset Conflict of Interest: Successful candidates for this job must satisfy the Company’s Conflict of Interest (COI) assessment process. Additional Information: This requisition is for a, locally hired position in Canada. The employer is Boeing Canada. Candidates must be legally authorized to work in Canada. Benefits and pay are determined by Canada and are not on Boeing US-based payroll. This is not an expatriate assignment. Please note that the information shown below is a general guideline only. Pay is based upon candidate experience and qualifications, as well as market and business considerations. Salary pay range - $101,000.00 – $179,000.00 CAD To review the Canadian Controlled Goods and Public Service and Procurement Canada requirements please go to the following government pages below: https://www.canada.ca/en/public-services-procurement/services/industrial-security.html https://www.tpsgc-pwgsc.gc.ca/esc-src/personnel/pdcf-rsrp-eng.html Language Requirements: Not Applicable Education: Not Applicable Relocation: Relocation assistance is not a negotiable benefit for this position. Security Clearance: This position requires an active or ability to obtain Canadian Government Controlled Goods Program (CGP) assessment. Visa Sponsorship: Employer will not sponsor applicants for employment visa status. Contingent Upon Award Program This position is not contingent upon program award Shift: