Data Engineer, Data Platforms

The Data Engineer, Data Platforms is a pivotal role on our Data Team - with broad responsibility. You're not just managing data; you're pioneering the very platforms that underpin our data and analytics engineering pursuits across the company's extensive landscape. You will own state-of-the-art big data platforms that power the Global Partners data stack -- with your work standing as the backbone supporting all data-centric innovations.You are fluent with platforms like AWS, Snowflake, Dagster, and dbt at your fingertips, and deploying via tools such as Kubernetes, Docker, and Terraform being second nature, you are primed to spearhead our pursuit of data excellence. Your vast experience, extending from data storage best practices to continuously assessing and integrating new technologies, ensures that Global Partners stays ahead of the curve.At the heart of it all, you're not just an engineer; you see the art in orchestrating data. As you engage with teams, provide strategic guidance, and champion the consistent adoption of best practices, you're also shaping the future of data analytics. If you're ignited by the prospect of being at the helm of technological evolution, where every decision melds strategy with data - Join us. Global Partners offers a collaborative team and an environment where we actively invest to create a culture of data driven excellence.The Types of “Energy” You BringExcellent written and verbal communication skills.You are self-motivated and like to take initiative.You are a team player with a positive attitude.You have strong time management skills.“Gauges” of ResponsibilityArchitect and implement scalable, cloud-native data platforms that serve as the foundation for all data engineering initiatives across the organization, utilizing technologies such as AWS, GCP, or Azure.Design and develop CI/CD pipelines for data infrastructure and applications, leveraging tools like Jenkins, GitLab CI, or GitHub Actions to ensure rapid, reliable deployments.Implement Infrastructure as Code (IaC) practices using tools such as Terraform or CloudFormation to manage and version control cloud resources.Develop and maintain robust data orchestration workflows using modern tools like Apache Airflow, Dagster, or Prefect, ensuring efficient data processing and transformation.Collaborate with security teams to implement and maintain IAM policies, user group management, and fine-grained access controls across data platforms and tools.Design and implement data cataloging and metadata management solutions to enhance data discovery, lineage tracking, and governance, utilizing tools like Apache Atlas or Collibra.Optimize data storage and processing systems, including data lakes and data warehouses (e.g., Snowflake, BigQuery, Redshift), to ensure cost-effectiveness and performance at scale.Develop automated tools and self-service platforms that enable data scientists and analysts to efficiently set up, configure, and monitor their data environments.Implement observability and monitoring solutions for data pipelines and infrastructure using tools like Prometheus, Grafana, or DataDog to ensure system reliability and performance.Lead the adoption of DataOps practices, fostering collaboration between data engineering, data science, and operations teams to streamline the entire data lifecycle.Design and implement data quality frameworks and automated testing processes to ensure data integrity and reliability across the organization.Continuously evaluate and integrate emerging technologies and best practices in big data, cloud computing, and DevOps to drive innovation and efficiency in data engineering processes.“

Fuel” for YouCoins!

We offer competitive salaries and opportunities for growth. We mean it! We have an amazing Talent Development Team who create trainings for growth and job development.Health + Wellness

- Medical, Dental, Visions and Life Insurance. Along with additional wellness support.The Road Ahead

– We offer 401k and a match component!Professional Development

- We provide tuition reimbursement; this benefit is offered after 6 months of service.Give Back!

We believe in community support. We know everyone gives in their own way, that’s why we offer paid volunteer time-off to you to help an organization of your choice.QUALIFICATIONSBachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent experience in Data Engineering, DataOps, MLOps, Software Engineering with a minimum of three year’s experience or 5 year’s experience, in lieu of an applicable degree.Strong proficiency in designing and implementing scalable, cloud-native (containerized) data platforms using Infrastructure as Code (e.g., Terraform, Docker, Kubernetes).Advanced programming skills in Python focusing on data-intensive applications. Strong SQL proficiency and experience with cloud data warehouses (e.g., Snowflake, BigQuery) required.Proven track record in designing and implementing CI/CD pipelines for data infrastructure and applications, using tools like Jenkins, GitLab CI, or GitHub Actions.In-depth knowledge of big data technologies (e.g., Apache Spark, Kafka) and data orchestration tools (e.g., Apache Airflow, Dagster). Experience with data transformation frameworks like dbt and ETL/ELT processes in cloud environments.Strong background in data security, governance, and metadata management. Experience implementing IAM/RBAC policies, encryption, and data access controls in cloud environments.Proficiency in implementing monitoring, logging, and alerting solutions for data infrastructure (e.g., Prometheus, Grafana, ELK stack). Familiarity with serverless architectures is a plus.Ability to design and develop automated tools and self-service platforms enabling efficient data environment setup and management for data scientists and analysts.Experience in optimizing data storage and processing systems for cost-effectiveness and performance at scale. Familiarity with MLOps and integrating ML models into production.Exceptional team player with strong communication skills, ability to work with cross-functional teams, and a willingness to mentor and share knowledge.Proficiency in modern Agile development methodologies, coupled with excellent problem-solving abilities and a metrics-first mindset.

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