The Senior Sales Engineer will serve as the primary technical expert for Securiti AI and Veeam solutions during the pre-sales cycle, translating customer risks and goals into practical solution designs. This involves leading technical conversations, designing and delivering tailored demonstrations, and executing hands-on proof-of-concepts to showcase product value.
Remote Data Engineer Jobs (2,552)
Search = Data Engineer
Principal Data Engineer (Research, Manufacturing, Supply Chain) - REMOTE
Vertex Inc.
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Full Time
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10 Weeks Ago
Vertex Inc.
The Principal Data Engineer will lead and manage the Data Engineering team to develop, curate, and maintain data assets supporting scientists, manufacturing, and supply chain teams. This involves integrating and curating data from research systems to enable analytics, modeling, and machine learning, while managing the Vertex Data Platform solutions.
This role involves owning the event ingestion and identity layer, focusing on the operational reliability and correctness of event and identity data moving through the data platform. Responsibilities include designing and operating pipelines, implementing schema validation, and building workflows to ensure product events are consistent and safe for analytics and reporting.
The Senior Data Engineer will lead the design and implementation of scalable, robust data architectures and build complex ETL/ELT pipelines integrating data from diverse sources. This role involves owning high-impact projects end-to-end, providing technical leadership, and enforcing data engineering best practices.
The Senior Data Engineer will be responsible for architecting and maintaining cutting-edge data systems to power analytics, AI, and operational decision-making across end-to-end data lifecycles. This includes designing scalable, cloud-native data architectures and developing efficient pipelines and models for batch and streaming use cases.
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The Senior Data Engineer will be responsible for architecting and maintaining cutting-edge data systems to power analytics, AI, and operational decision-making across end-to-end data lifecycles. This includes designing scalable, cloud-native data architectures and developing efficient ETL/ELT pipelines supporting real-time insights and machine learning at scale.
The Senior Data Engineer will be responsible for architecting and maintaining cutting-edge data systems to power analytics, AI, and operational decision-making across end-to-end data lifecycles. This includes designing scalable, cloud-native data architectures and developing efficient pipelines and models for batch and streaming use cases.
The role involves designing, developing, and maintaining robust and scalable data pipelines using ETL/ELT processes. Responsibilities also include building and optimizing data architectures and models while ensuring high data quality and reliability across systems.
The role involves owning the data pipeline from BMS ingestion through the analytics layer, focusing on data reliability, quality, and real-time streaming infrastructure for ML models. Key tasks include building ingestion bridges for industrial protocols (OPC-UA, BACnet, MQTT) and managing data storage solutions like TimescaleDB and MinIO/S3.
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 data. Responsibilities also include monitoring performance metrics and playing a key role in implementing security best practices.
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.
The Senior Data Engineer will be responsible for designing, developing, and maintaining scalable data pipelines primarily using Apache Spark and building optimized data workflows within Databricks environments. This includes ingesting, transforming, and curating large-scale datasets while ensuring performance tuning and data quality.
The engineer will architect, deploy, and scale robust data pipelines moving data between Datomic, Kafka, and BigQuery, while also building fault-tolerant ETL systems to normalize messy data from various APIs.
The role involves building and owning data pipelines and ETL processes for claims ingestion, pricing, and CRM synchronization, while designing warehouse schemas and transforms that support the entire company. Key tasks include maintaining data quality, building live reporting systems for various teams, and developing PHI-safe infrastructure to feed AI/LLM workloads.
The Senior Data Engineer will analyze, design, and develop solutions focused on data engineering and ETL workflows, collaborating with stakeholders to understand business needs and guide outcomes. This role involves driving the organizational data strategy, establishing data engineering standards, and leading the creation and maintenance of technical documentation and architecture diagrams.
The role primarily focuses on ETL responsibilities, managing processes to extract, transform, and load data from multiple sources into a data warehouse while troubleshooting data errors. The remaining portion involves AI data wrangling, preparation, and applying ML models to gain insights and augment AI strategies.
The role involves designing, implementing, and maintaining scalable solutions with a focus on data pipelines and automation within a cloud-native environment. Responsibilities include building intuitive user experiences for data querying and visualization, ensuring high availability for customer systems, and providing direct customer support.
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The role involves building, scaling, and maintaining robust data solutions by implementing and optimizing high-performance data pipelines for extraction, loading, transformation, and orchestration. Primary duties also include championing modern software engineering practices and collaborating with stakeholders to deliver production-ready services.
Engineers will design, develop, and implement robust, scalable, and cloud-native data and AI solutions contributing directly to the company's mission. They will write clean, well-tested code, participate in reviews, and contribute across the stack including backend services and AI features.
The Data Engineer will be responsible for developing and maintaining data pipelines, transformation logic, and data quality checks within a complex multi-jurisdiction financial data platform. This includes implementing enhancements to existing reporting processes and designing new reporting pipelines aligned with business requirements.
The Senior Data Engineer will be responsible for designing, building, and maintaining scalable data pipelines for analytics and decision-making, focusing on both batch and streaming architectures using PySpark and SQL on GCP. Key duties include defining data architecture on GCP (BigQuery, Cloud Composer), designing data models for insurance data (Guidewire), and establishing data governance and quality frameworks.
The role involves working as a Data Engineer focusing on Google Cloud Platform tools, including building ETLs, data modeling, and query optimization within BigQuery. Responsibilities also include creating and maintaining workflows using Airflow, managing version control with GIT, and potentially maintaining legacy Big Data systems.
The role involves designing, developing, and maintaining scalable data pipelines using Databricks (PySpark) and Python within Azure environments, focusing on building ETL/ELT processes and implementing Data Lakehouse principles.
Senior Software Engineer - Data & AI Security
Orca Security
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Full Time
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11 Weeks Ago
Orca Security
The role involves designing, implementing, and maintaining scalable backend services for scanning and analyzing managed databases, object storage, and data assets across cloud providers. Responsibilities also include building infrastructure for detecting sensitive data, secrets, and keys, and mapping/assessing cloud AI services for security posture.
Staff Data Engineer - Exclusive Opportunity for Women
Blip Global
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Full Time
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11 Weeks Ago
Blip Global
The Staff Data Engineer will design, implement, and optimize high-throughput, low-latency data pipelines processing billions of daily events, ensuring fault-tolerance and exactly-once semantics. They will also champion data modeling excellence across streaming, analytical, and serving layers, partnering with architects to ensure data quality and traceability.
Forward Deployed Engineer - Data Migration & Data Consolidation Platforms
Rackspace Technology
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Full Time
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11 Weeks Ago
Rackspace Technology
The role involves leading end-to-end execution of complex data migrations and multi-system consolidations for global enterprises, acting as both solution architect and hands-on implementer. Key duties include designing cloud architecture, building automated data pipelines with LLM logic, and developing semantic ontology layers to unify fragmented application landscapes.
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The role involves designing, developing, and maintaining robust and scalable data pipelines, integrating heterogeneous data sources, and ensuring data quality. Responsibilities also include collaborating with analytics and product teams and optimizing data ingestion, transformation, and storage processes.
The role involves designing, building, and optimizing ETL pipelines using Microsoft Fabric and Medallion Architecture to power data-driven decisions across the firm. Responsibilities also include improving infrastructure scalability, monitoring data quality, and supporting business intelligence tools.
The Lead Data Engineer will be responsible for architecting, scaling, and maintaining the data ecosystem, transforming raw signals into actionable intelligence to support rapid growth. Key deliverables include leading data infrastructure design, ensuring scalability and performance, and integrating AI-driven models into production workflows.
The role involves designing, implementing, and maintaining data pipelines utilizing Python and SQL, orchestrated through Airflow for monitoring data workflows. Responsibilities also include collaborating with stakeholders to translate data requirements into robust, well-documented implementations.
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