The role focuses on building and maintaining GIS data workflows to acquire, clean, and transform geospatial datasets. It involves ensuring data quality and reliability to support product engineering, analytics, and machine learning workflows.
Remote Data Engineer Jobs (2,742)
Search = Data Engineer
The role involves designing and implementing complex ETL/ELT pipelines and leading data warehousing projects for clients. It requires collaborating with internal and external teams to deliver data integrations and real-time processing solutions.
Lead the design and implementation of complex ETL/ELT pipelines and data warehousing projects for clients. Collaborate with internal and external stakeholders to deliver data integrations and real-time processing solutions.
The role involves designing and implementing complex ETL/ELT pipelines and leading data warehousing projects in a client-facing environment. Responsibilities include collaborating with internal and partner teams to deliver data integrations and real-time processing solutions.
The Senior Data Engineer designs and manages the enterprise data foundation, creating secure, AI-enabled data products and pipelines to support a regulated pharmacy environment. They are responsible for platform architecture, data modeling, and establishing high engineering standards for observability and deployment.
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Data Engineer (DBT) (m/f/d)
synvert Portugal(Recruiting)
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Full Time
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6 Weeks Ago
synvert Portugal(Recruiting)
The Data Engineer will lead a quality-driven migration of data pipelines, focusing on improving structure and reliability rather than a simple lift-and-shift. Key tasks include mapping dependencies, ensuring PII compliance, and implementing robust data quality tests and monitoring.
Data Engineer (DBT) (m/f/d)
synvert Portugal(Recruiting)
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Full Time
·
6 Weeks Ago
synvert Portugal(Recruiting)
Lead the quality-driven migration of data pipelines by engaging with dataset owners and optimizing existing queries. Establish data quality tests, monitoring infrastructure, and ensure security compliance for PII fields.
Design, build, and optimize scalable data pipelines to transform raw data into actionable insights. Lead the evolution of data infrastructure while ensuring high performance and reliability across cloud environments.
Design and implement scalable ETL/ELT pipelines and modern data platforms using Databricks and Azure. Collaborate with architects and stakeholders in an Agile environment to deliver analytics-ready datasets for BI and AI workloads.
Design, develop, and maintain scalable ETL/ELT data pipelines to support analytics and machine learning initiatives. Collaborate with data scientists and analysts to optimize database performance and ensure secure data delivery.
Drive the end-to-end development of core data infrastructure using AI-native engineering and agentic workflows. Design and optimize high-throughput, real-time streaming pipelines while mentoring junior engineers to ensure technical excellence.
Lead the design and implementation of scalable data pipelines while mentoring fellow data engineers. Partner cross-functionally with Product and DevOps teams to drive analytics innovation and optimize cloud infrastructure.
Design and build scalable data pipelines and models to create a digital twin of Nscale's operational signals. Develop trusted datasets and metrics to enable self-serve analytics for capacity planning and cost optimization.
Own the end-to-end delivery of AI-automated data platform migration projects, including scoping, planning, and execution. Act as the primary customer contact to manage expectations and partner with engineering teams to refine the delivery playbook.
![Software Mind is hiring for remote [C3C] Senior Data Engineer (Python)](/assets/2083550c-5c59-4fae-b76e-a23e4817e5f2.jpeg){kind=small}
Design and implement scalable data capabilities, including ingestion pipelines and high-performance APIs, for a proprietary cyber insurance data platform. Collaborate with cross-functional teams to evolve the architecture toward a data mesh and maintain high data quality standards.
Design and implement scalable data pipelines and ETL/ELT processes using GCP services like Dataflow and BigQuery. Collaborate with clients to translate business needs into technical data solutions while optimizing performance and costs.
Design, develop, and deploy data solutions, including the creation of dashboards and reports to provide business insights. Manage data ingestion, ETL processes, and performance tuning for complex SQL and DAX queries.
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Design, build, and optimize scalable data processing systems and ETL/ELT pipelines within cloud and on-prem environments. Support the migration of legacy DWH systems to a Data Mesh platform while ensuring data quality and security.
Design and implement modern data platforms, scalable pipelines, and analytics solutions using Microsoft Fabric and Databricks. Develop ETL/ELT processes and maintain medallion architectures to enable data-driven decision making.
The role involves migrating data transformations from Pentaho to dbt and modernizing existing data models. The engineer will build and optimize SQL-based ELT pipelines within a Google Cloud Platform environment.
Development Engineer - Data Centers
NEI Electric Power Engineering
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Full Time
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6 Weeks Ago
NEI Electric Power Engineering
Execute early-stage project development, feasibility studies, and preliminary designs for complex electrical infrastructure. Act as a technical liaison between internal design teams, business development partners, and external stakeholders.
Data Engineer (REF5482T)
Deutsche Telekom IT Solutions
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Full Time
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6 Weeks Ago
Deutsche Telekom IT Solutions
Develop and optimize scalable data pipelines and warehouses to support electronic road-charging solutions. Collaborate with data scientists and analysts to ensure data quality, security, and high-performance analytics operations.
Lead Data Engineer with Google cloud GCP (m/f/d)
Deutsche Telekom IT Solutions Slovakia
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Full Time
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6 Weeks Ago
Deutsche Telekom IT Solutions Slovakia
Lead the design, construction, and maintenance of scalable data pipelines and infrastructure on GCP. Mentor a team of data engineers while collaborating with stakeholders to deliver reliable data products from the ground up.
Lead Data Engineer (m/f/d)
Deutsche Telekom IT Solutions Slovakia
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Full Time
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6 Weeks Ago
Deutsche Telekom IT Solutions Slovakia
Manage and oversee the entire data engineering process, from acquisition to analysis, while designing and maintaining scalable data infrastructure. Lead and mentor a team of data engineers to ensure the successful delivery of projects and technical direction.
Lead the migration of legacy data systems to a Kimball/star schema architecture and drive platform modernization. Design and maintain production-grade data pipelines while enforcing data hygiene and quality standards.
Build and operate the data infrastructure and ETL pipelines to track cost, margin, and performance across production systems and vendor APIs. Partner with infrastructure and product teams to define data contracts and implement low-latency analytical write paths.
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Establish and own the entire data stack by consolidating disparate data sources into a single BigQuery warehouse. Build AI-powered internal data tools and a data lake architecture to support product personalization and model fine-tuning.
Optimize and scale Snowflake architecture while implementing agentic engineering and MLOps pipelines. Develop enterprise-wide semantic models and establish robust data observability frameworks to ensure pipeline reliability.
The role focuses on optimizing Snowflake architecture and implementing agentic engineering to automate workflows and build semantic models. You will also be responsible for establishing data observability frameworks and operationalizing MLOps pipelines to support machine learning models.
Drive the delivery and support of data and AI applications by designing and scaling data pipelines across various source systems. Collaborate with cross-functional teams to implement design patterns that optimize performance, cost, and security for analytics stakeholders.
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