As an Data Engineer, you will work closely with a multidisciplinary Agile team to build high quality data pipelines driving analytic solutions. These solutions will generate insights from our connected data, enabling Element to advance the data-driven decision-making capabilities. This role requires deep understanding of data architecture, Data Engineering, data analysis, reporting, and a basic understanding of data science techniques and workflows. The ideal candidate is a skilled data / software engineer with experience creating data products supporting analytic solutions. They are an Agile learner, possess strong problem-solving skills, work as part of a technical, cross functional analytics team, and want to Solve complex data problems and deliver the insights to enable analytics strategy.
Responsibilities:
- Design, develop, optimize, and maintain data architecture and pipelines that adhere to ETL principles and business goals
- Solve complex data problems to deliver insights that helps our business to achieve their goals
- Create data products for analytics and data scientist team members to improve their productivity
- Advise, consult, mentor and coach other data and analytic professionals on data standards and practices
- Foster a culture of sharing, re-use, design for scale stability, and operational efficiency of data and analytical solutions
- Lead the evaluation, implementation and deployment of emerging tools and process for analytic Data Engineering in order to improve our productivity as a team
- Develop and deliver communication and education plans on analytic Data Engineering capabilities, standards, and processes
- Partner with business analysts and solutions architects to develop technical architectures for strategic enterprise projects and initiatives.
- Learn about machine learning, data science, computer vision, artificial intelligence, statistics, and/or applied mathematics
- Bachelor’s degree required; Computer Science, MIS, or Engineering preferred
- 5 years of experience working in Data Engineering or ML engineering role
- Proficient with at least one programming language (Python preferred)
- Expertise in production grade ETL pipeline development and data analysis
- Experience with developing solutions on cloud computing services and infrastructure in the data and analytics space (Azure stack, Kubernetes)
- Database development experience using Hadoop or BigQuery and experience with modern DB technologies such as: PostgreSQL, NoSQL, Embedding DBs and cloud native database solutions
- Experience with ML lifecycle tools such as model registries & automated model monitoring frameworks
- Conceptual knowledge of data and analytics, such as dimensional modeling, ETL, reporting tools, data governance, data warehousing, structured and unstructured data.
- Worked with BI tools such as Tableau, Power BI, Looker, Shiny
- Exposure to event driven architectures, scheduling frameworks & APIs
- Exposure to machine learning, data science, artificial intelligence, and/or applied mathematics
- Passionate about Agile software processes, data-driven development, reliability, and experimentation
- Experience working on a collaborative Agile product team
When failure in use is not an option, we help customers make certain that their products, materials, processes and services are safe, compliant and fit for purpose. From early R&D, through complex regulatory approvals and into production, our global laboratory network of scientists, engineers, and technologists support customers to achieve assurance over product quality, sustainable outcomes, and market access.
While we are proud of our global reach, working at Element feels like being part of a smaller company. We empower you to take charge of your career, and reward excellence and integrity with growth and development.
Industries across the world depend on our care, attention to detail and the absolute accuracy of our work. The role we have to play in creating a safer world is much bigger than our organization.
All suitably qualified candidates will receive consideration for employment on the basis of objective work related criteria and without regard for the following: age, disability, ethnic origin, gender, marital status, race, religion, responsibility of dependents, sexual orientation, or gender identity or other characteristics in accordance with the applicable governing laws or other characteristics in accordance with the applicable governing laws.