Data Engineer (Snowflake)
Design, build, and maintain scalable data pipelines and cloud data solutions using Snowflake. Collaborate with engineering and analytics teams to ensure high-quality data availability for reporting and decision-making.
Remote Data Engineer Jobs in Finland
92 Data Engineer jobs in Finland available for remote work from home. Apply for positions such as Data Engineer (Snowflake), Senior Software Engineer (Data), Data Engineer (Databricks | AWS | AI/RAG) and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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Design, build, and maintain scalable data pipelines and cloud data solutions using Snowflake. Collaborate with engineering and analytics teams to ensure high-quality data availability for reporting and decision-making.
You will design and build new cost-management features, including forecasting, anomaly alerts, and data-visualization tools. Additionally, you will develop data pipelines and transformation models while ensuring the reliability and performance of the application.
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.
Design and maintain scalable ETL/ELT pipelines and data workflows while ensuring data quality and security. Contribute to the development of voice-agent solutions, including speech-to-text, text-to-speech, and LLM integrations.
The engineer will analyze existing Power BI reports and Alteryx workflows to document end-to-end data lineage and transformation logic. They will also collaborate with stakeholders to validate report logic and identify obsolete data sources.
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Design and operate high-volume, low-latency real-time data systems using Apache Flink as the core engine. Build and maintain high-scale streaming data pipelines on self-managed on-premise infrastructure.
Design and operate high-volume analytical data systems end to end using Apache Spark. Build and maintain high-scale batch and near-real-time data pipelines on self-managed infrastructure.
Design, implement, and maintain web scrapers to collect alternative datasets while performing data cleaning and transformation. Collaborate with cross-functional teams to build efficient data processing workflows and maintain alerting systems for data integrity.
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.
Design, build, and maintain scalable data pipelines while leveraging tools like Azure Data Factory and Databricks. Lead and mentor engineering teams while collaborating with cross-functional stakeholders to deliver comprehensive data solutions.
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 build scalable data ingestion, cleaning, and LLM enhancement pipelines to power AI applications. Implement AI guardrails and RAG architectures to ensure the accuracy and reliability of AI-ready datasets.
Design and maintain scalable data pipelines using Databricks to support HR and People Analytics. Develop interactive Power BI dashboards and optimize data models to provide actionable workforce insights.
The Senior Mechanical Engineer will design solutions and perform calculations for large technology companies and mission-critical clients. Responsibilities include writing technical reports, preparing documents, and coordinating with internal teams and clients.
Build and scale data platforms for AI-driven analytics using high-volume sensor, satellite, and third-party data. Own end-to-end data pipelines from real-time ingestion to analytics while ensuring data quality and performance.
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Lead the implementation of a scalable data quality and observability framework using GX Core to detect and prevent data issues. Design automated validation checks, maintain data lineage, and integrate quality validations into CI/CD pipelines.
Design, develop, and deploy scalable data pipelines and ETL/ELT processes using the Dataiku DSS platform. Support a large-scale enterprise data lakehouse migration while collaborating with international business and technical stakeholders.
Architect and maintain the data model, pipelines, and access layers to support healthcare operations and analytics. Lead technical engineering best practices and ensure data quality and governance across the platform.
Design and optimize robust data pipelines and scalable warehousing architectures using Snowflake and dbt. Collaborate with stakeholders to transform raw data into actionable models for manufacturing and supply chain workflows.
Develop and maintain the Enterprise Data Warehouse and standard dashboards for a Global Business Intelligence Team. Provide data support for business self-service and data analysis activities.
Design and maintain scalable ETL/ELT pipelines to extract and load data from sources like Oracle. Create and optimize data models in Snowflake and Redshift to support AI/ML solutions and business objectives.
Design, develop, and deploy bots using Automation Anywhere A360 and Excel VBA macros. Collaborate with stakeholders to identify automation opportunities and maintain documentation such as PDDs and SDDs.
Design and maintain scalable batch and real-time data pipelines on GCP using Medallion Architecture. Develop high-performance data transformations and optimize complex SQL queries for large-scale analytical workloads.
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.
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Design, develop, and optimize AI/ML models and pipelines to power cybersecurity behavioral detectors. Collaborate with cross-functional teams to integrate these features into a scalable, fault-resilient platform.
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 instrumentation and control systems for data centers, including conceptual designs, detailed site designs, and retrofits. Coordinate with multidisciplinary teams and vendors to ensure Building Management Systems are properly designed and constructed.
Architect and maintain scalable data platform infrastructure and optimize analytic query engines. Collaborate with data teams to implement robust data management solutions and observability frameworks.
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