Design and deliver enterprise-scale data platforms on Microsoft Azure and Databricks, including data lake, warehouse, and lakehouse architectures, governance, security, and technical leadership.
Responsibilities
Design scalable data lake, data warehouse, and lakehouse architectures on Azure and Databricks
Define Databricks architecture covering Unity Catalog, Delta Lake, Workflows, SQL Warehouses, Lakeflow, notebooks, AI/ML and model serving
Design networking, identity and access management, security, governance, monitoring, and environment strategies
Define data integration patterns for batch, streaming, APIs, messaging, and data virtualization
Establish infrastructure automation, deployment standards, performance optimization, and cost management
Oversee and enhance data services within Continental’s Digital Solutions IT team, building and maintaining cloud-based data platforms, pipelines, and streaming solutions.
Responsibilities
Support and maintain cloud-based data platforms, pipelines, and streaming solutions
Develop and enhance batch and real-time data pipelines
Monitor, troubleshoot, and resolve data and platform issues
Support CI/CD, deployment, and automation processes
Collaborate with stakeholders to understand and deliver data requirements
Requirements
University degree in Computer Science, IT, or related studies
Lead end-to-end analytical projects, build dashboards, develop reproducible workflows, and drive data-driven decision-making for product strategy and monetization.
Compensation
The salary range for this role in Vilnius is EUR 4500-5600 monthly gross.
Responsibilities
Lead exploratory analysis and apply statistical methods to solve complex product and business problems
Work autonomously on end-to-end analysis projects focused on product metrics, feature impact, player behavior, and opportunities to improve engagement, retention, monetization, or product health
Define and maintain product metrics, ensuring consistent KPI definitions and clear relationships between engagement, retention, monetization, and overall product health
Build dashboards and reports that support product, business, and operational decisions
Develop reproducible analytical workflows using modern analytics tools (Python/R, AB test platforms, BI tools, AI)
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
This job will develop and implement data science models and algorithms to support business needs.
Compensation
The base pay for this role will depend on where you work and the relevant experience and expertise you bring. The expected range of pay for this role by location is: Primary Location | Pay Range: Tokyo, Tokyo Prefecture; (¥6,215,000.00 - ¥8,888,000.00 Annually)
Responsibilities
Develop and implement data science models and algorithms
Analyze and interpret complex data sets
Ensure data quality and integrity
Collaborate with stakeholders to understand data requirements
Optimize data processes for efficiency and performance
Requirements
Bachelor’s degree
Nice to have: experience extracting insights and engineering features from large datasets (clickstream data, app activity data, streaming service logs)
Nice to have: experience working with a BI tool like Looker, Tableau
Nice to have: experience developing predictive models applied to real-world business problems in technology industry
Nice to have: experience working with production ML pipelines with a managed service like Sagemaker
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