Senior Data Engineer responsible for designing, developing, testing, deploying and monitoring data pipelines in Databricks on AWS, building scalable code with PySpark and SQL, improving internal processes, creating data quality dashboards, and ensuring data security and governance.
Locations (2)
Ho Chi Minh City, Ho Chi Minh City (HCMC), Vietnam
Hanoi, Hanoi, Vietnam
Compensation
Performance-based bonus and equity participation in GoTyme Group
13th month salary pro-rata
Responsibilities
Design, develop, test, deploy and monitor data pipelines in Databricks on AWS
Design, develop, test, deploy and monitor scalable code with PySpark and SQL in Databricks
Identify opportunities to improve internal process through code optimisation and automation
Build data quality dashboards, lineage flows and monitoring tools
Assist in migrating data from legacy systems onto newly developed solutions
Help build the modern data processing platform behind proactive network monitoring — a core capability of the managed network services product used across thousands of enterprise and government sites.
Responsibilities
Design, build, and operate reliable, scalable, data-intensive pipelines carrying high-volume device and network telemetry
Build and evolve stateful, real-time event processing that transforms raw telemetry into meaningful operational events at scale
Extend and enhance the detection and workflow engine to support client-specific flow paths and parameters
Partner with product and front-end engineers to expose event and incident monitoring flow in the product experience
Instrument the platform so engineers can trace events end-to-end and understand system behavior
Requirements
Degree in Computer Science, Engineering, or equivalent experience
As Associate Director, Cloud Data Platform Architecture, you will define the technology strategy and architecture for cloud data platforms supporting the Novartis Drug Development portfolio.
Compensation
Expected Annual Base Salary Range: €63,800 – €118,400 EUR
Responsibilities
Lead the architecture and design of cloud data platform capabilities supporting Drug Development use cases
Define technology strategy, architecture standards and reusable platform patterns
Guide the evolution of the existing multi-tenant cloud data mesh platform
Partner with Domain IT, Platform Engineering, Data Management, Governance and external vendors
Prioritise capability backlogs, shape delivery roadmaps and coordinate MVP delivery
Requirements
Degree in Information Technology, Life Sciences, Pharmacy, Engineering or equivalent
Nice to have: Experience in pharmaceutical, life sciences or drug development environments
Nice to have: Familiarity with data mesh architecture
Nice to have: Experience defining reference architectures
Nice to have: Experience with vendor architects and SLAs
Design, build, and deploy scalable and secure data engineering pipelines using Databricks on Azure, collaborating with clients and cross‑functional teams.
Locations (2)
Glasgow, Scotland, United Kingdom
Edinburgh, Scotland, United Kingdom
Responsibilities
Design and develop robust pipelines using DeltaLake, Spark Structured Streaming, and Unity Catalog
Build real‑time event‑driven solutions with Kafka and Azure Event Hubs
Apply DevOps principles to develop CI/CD pipelines using Azure DevOps, Jenkins, or GitHub Actions
Collaborate with clients and stakeholders to translate data needs into strategic technical solutions
Champion clean code, data lifecycle optimisation, and software engineering best practices
Design, build, and deploy scalable and secure data engineering pipelines using Databricks on Azure, collaborating with clients and stakeholders to translate data needs into strategic solutions.
Locations (2)
Glasgow, Scotland, United Kingdom
Edinburgh, Scotland, United Kingdom
Responsibilities
Design and develop robust pipelines using DeltaLake, Spark Structured Streaming, and Unity Catalog
Build real-time event-driven solutions with Kafka and Azure Event Hubs
Apply DevOps principles to develop CI/CD pipelines using Azure DevOps, Jenkins, or GitHub Actions
Collaborate with clients and stakeholders to translate data needs into strategic technical solutions
Champion clean code, data lifecycle optimisation, and software engineering best practices
Lead Data Engineer role focused on driving the modernization of a large-scale reconciliation data platform from legacy Hadoop to Databricks on AWS using Scala Spark and cloud-native patterns.
Responsibilities
Build and optimise large-scale Scala Spark data pipelines on Databricks, focusing on the reconciliation domain — writing clean, modular, and production-ready code
Drive modernisation efforts by refactoring legacy Hadoop-based pipelines into cloud-native Databricks/AWS architectures using Delta Lake and Databricks Workflows
Tune and simplify complex or over-engineered Spark jobs — analysing performance bottlenecks and transforming them into efficient, standardised patterns
Translate designs into reality — take high-level architectural decisions and convert them into detailed technical implementations, data models, and reusable pipeline components
Collaborate daily with architects, platform, and DevOps teams on design discussions, technical decisions, and production releases
Building and optimising large-scale Scala Spark data pipelines on Databricks for the enough domain, driving modernization from legacy Hadoop to AWS cloud architecture.
Responsibilities
Build and optimise large-scale Scala Spark data pipelines on Databricks
Drive modernisation efforts by refactoring legacy Hadoop-based pipelines into cloud-native Databricks/AWS architectures
Tune and simplify complex or over-engineered Spark jobs
Translate architectural deisions into detailed technical implementations and data models
Collaborate daily with architects, platform, and DevOps teams
Associate AI/ML EngineerUnitedHealth Group