DATA ENGINEER
Build and maintain scalable data pipelines, platforms, and models to create tangible business value for customers. Translate business requirements into actionable technical tasks within modern cloud ecosystems.
26 Data Engineer jobs in Finland available for remote work from home. Apply for positions such as DATA ENGINEER, Senior Data Engineer, Principal Data Engineer and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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Build and maintain scalable data pipelines, platforms, and models to create tangible business value for customers. Translate business requirements into actionable technical tasks within modern cloud ecosystems.
You will design and implement modern data solutions, including data ingestion, modelling, and pipeline development on cloud platforms. You will also collaborate with customers to make architectural decisions and build reliable, scalable data systems.
The Principal Data Engineer will design, develop, and support SAP HANA reporting solutions for special projects. They will partner with stakeholders to translate strategic business needs into effective data products and interactive visualizations.
You will build and maintain backend services and APIs while designing reliable data ingestion and processing workflows. Additionally, you will collaborate with cross-functional teams to ensure data accuracy, consistency, and availability across the platform.
The role involves managing data collection and ingestion pipelines to support AI model training operations. You will collaborate with scientists and leadership to optimize data infrastructure and define the dataset roadmap.
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Design, build, and operate scalable batch and streaming data pipelines using Python, PySpark, and Azure Databricks. Manage data architecture, orchestration, and CI/CD processes while ensuring high data quality and performance.
You will design and evolve scalable, cloud-native data architectures on AWS while providing technical leadership to engineering teams. Additionally, you will collaborate on AI-ready data platforms and establish best practices for data quality, governance, and performance.
The role involves managing data collection and ingestion pipelines to support large-scale model training operations. You will collaborate with scientists and leadership to optimize data infrastructure and define the dataset roadmap for AI products.
Design, build, and maintain scalable data ingestion pipelines using AWS Glue to move data into Amazon S3. Ensure data integrity, manage medallion architecture layers, and optimize pipeline performance and costs.
Lead and review the electrical design of hyperscale and mission-critical data centres across all project phases while managing multidisciplinary external consultants. Oversee utility coordination, permitting, and integrated systems testing to ensure project delivery meets design intent and operational requirements.
You will maintain and enhance ETL pipelines while managing data ingestion from diverse sources like S3, Azure Blob, and APIs. Additionally, you will investigate and resolve pipeline failures in a live production environment and support infrastructure migration to AWS.
You will own the end-to-end data ecosystem, including building reliable ETL/ELT pipelines and modeling data in dbt. Additionally, you will partner with stakeholders to define business metrics and implement observability for analytics pipelines.
You will own the technical delivery and platform reliability of cloud-native data environments on AWS and Azure for managed services clients. This involves building infrastructure-as-code, maintaining CI/CD pipelines, and collaborating with stakeholders to implement scalable, well-governed solutions.
The role focuses on building, maintaining, and optimizing scalable data pipelines and architectures to power business-critical analytics. It involves collaborating with Data Science and Ops teams to ensure data quality and enable self-service analytics.
Design and maintain scalable data pipelines and lakehouse architectures to process operational data. Collaborate with business stakeholders to translate requirements into clean, analytics-ready datasets for BI and machine learning.
Design and implement complex data solutions, architectures, and scalable pipelines for customers. Translate business requirements into technical tasks to help organizations capitalize on data and AI opportunities.
Design and build data pipelines to extract data from enterprise ERP systems and transform them through medallion architectures. Deliver governed, AI-ready data products while collaborating with business stakeholders to validate data models.
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Build and scale robust data solutions and high-performance pipelines for extraction, loading, and transformation. Collaborate with stakeholders to transform business use cases into production-ready services while ensuring data quality through rigorous testing.
Design and optimize data pipelines while collaborating with Data Science and Product teams. Contribute to building robust data solutions for top-tier companies across various regions.
The role involves taking ownership, improving, scaling, and iterating on existing data processing pipelines while also designing and implementing new ones for best-in-class road features and navigation. Responsibilities also include monitoring performance metrics and playing a key role in implementing security best practices.
Develop technical enablement content such as white papers, labs, and presentations to support product positioning and field teams. Design and maintain product demonstrations that showcase technical capabilities and business outcomes for Apstra.
You will architect and scale distributed web scraping systems to collect data from thousands of internet sources while ensuring reliable ingestion into a production-grade data product. Additionally, you will maintain the data access layer using GraphQL and collaborate with cross-functional teams to integrate ML components.
Own the reliability and correctness of core data products by managing end-to-end releases and building quality monitoring systems. Partner with commercial teams to design data solutions and perform root cause analysis on data anomalies.
Own and manage all databases underpinning the BSS/OSS/NOC platform, including PostgreSQL clusters and network control layer interfaces. Design and implement bulk data pipelines, disaster recovery frameworks, and data governance policies for compliance and retention.
The role involves monitoring ELT pipelines, maintaining data warehouse models, and developing business intelligence data models. It also focuses on improving data assets for AI workflows and supporting organization-wide analytics requests.
Develop comprehensive fire protection design solutions for data centers, including detection and suppression systems. Responsible for creating construction drawings, bills of quantities, and providing on-site technical guidance for project delivery.
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