Job Opportunities API

Having recognized the advantages of remote work, including employee morale, productivity, reduced commuting on employee wellbeing and the environment, we are proud to be a digital-first company. The technologies and programs in which we invested have provided a fantastic foundation to this end. Our digital-first work environment, together with our conveniently located offices and collaborative workspaces, provide our team with the freedom and flexibility to work in the way that makes our employees most productive. About us Tecsys is a fast-growing innovator offering supply chain solutions to industry leading healthcare systems, hospitals, and pharmacy businesses to distributors, retailers, and 3PLs. We work with industry leaders to transform their supply chains through technology. If you thrive on tackling interesting challenges with continuous learning opportunities, then Tescys could be a good fit for you! We're looking for a  Data Platform Engineer (DevOps)  to join our TecsysIQ Data & AI team. This is a hybrid role that builds and operates the cloud data platform powering our analytics and AI products on Databricks and AWS. You will own the infrastructure-as-code and delivery pipelines that provision and deploy the platform,  and  the Databricks jobs and streaming pipelines that move and shape data through it. You'll partner closely with Data Platform Developers, application dev teams, and Product Owners — standing up new customer environments, evolving the CI/CD and release process, and creating and maintaining the data pipelines that keep the platform running reliably at scale. If you are equally comfortable writing Terraform and debugging a Spark Structured Streaming job, this role is for you. Responsibilities Platform & DevOps Provision and evolve AWS and Databricks accounts and workspaces using  Terraform  across multiple regions and environments, managing remote state and per-environment configuration. Own the  Helm charts and Kubernetes Jobs  that onboard new customer environments and deploy the application layer onto provisioned workspaces. Build and maintain  Docker  images and the Java/Maven build pipeline, publishing artifacts to internal artifact and container registries. Integrate build, test, and deployment into  CI/CD pipelines , and improve release management and versioning across interdependent repositories. Manage secrets and credentials safely through cloud secret management and Kubernetes — never in source control. Data Platform & Pipelines Design, build, and maintain  Databricks jobs and pipelines  — including data curation, transformation, and initial bulk-load workflows. Develop and operate  real-time streaming and change data capture (CDC) pipelines  across the ingestion and transformation layers using  Spark Structured Streaming . Build and evolve end-to-end data movement across the  Bronze, Silver, and Gold  data layers, extending pipelines to handle new sources and schema changes as the platform grows. Develop and maintain reusable pipeline components and frameworks so new data workflows can be onboarded and shipped quickly. Tune clusters and SQL warehouses for cost and performance, and manage catalog, schema, and access governance across environments. Collaborate with Data Platform Developers, Product Owners, and business stakeholders in an Agile environment to deliver high-quality data products. Requirements Qualifications Hands-on experience with  Databricks  and  Apache Spark , including building batch or streaming data pipelines (mandatory). Strong  Terraform  skills and comfort managing cloud infrastructure on  AWS . Working knowledge of  Kubernetes  and  Helm , and containerization with  Docker . Proficiency in  Python  (PySpark) and/or  Java , plus strong SQL for data validation