Top Data Engineer Jobs
As a Senior Lead Data Engineer at Capital One, you will lead a team in building scalable data solutions, collaborating with agile teams, and leveraging big data technologies to transform data handling and enhance governance. You will design, implement, and support cutting-edge cloud solutions while mentoring engineers and ensuring code quality. The role focuses on addressing complex business problems with big data and cloud computing.
The Senior Data Engineer at Northwestern Mutual will apply engineering best practices to analyze, design, develop, deploy, and support software solutions. Responsibilities include developing software through continuous integration, participating in Agile practices, performing code reviews, and identifying data quality issues. The role requires a collaborative work environment and a strong understanding of data engineering concepts.
The Senior Data Engineer will design and implement ETL processes in a cloud environment, develop monitoring solutions, document datasets, and collaborate with the Data Science team. This role requires building ETL processes and a strong understanding of data modeling.
As a Product Data Engineer at xAI, you will utilize models and algorithms to develop innovative consumer products and experiences, scaling them to millions of global users. Responsibilities include data curation for large models, ensuring quality in human annotation, and using data to inform product direction.
As a Data Engineer at The Hartford, you will enhance and troubleshoot reserving applications, architect innovative solutions, optimize processes, and solve technical issues. You will manage research or project work while collaborating closely with business partners using Agile methodology.
As a Principal Data Engineer, you will design and build data ingestion pipelines, conceptualize high-performance data processing, and collaborate with multiple teams to deliver analytical solutions using Azure and big data technologies. You will also ensure the quality and scalability of your code while engaging with stakeholders across the organization.
The Data Engineer will architect, design, and implement advanced analytics capabilities while building and deploying large-scale data processing pipelines. Responsibilities include optimizing complex data processing and transformation pipelines, creating self-service dashboards, and collaborating with cross-functional teams to generate insights that drive business value.
As a PowerBI Data Engineer, you will extract and correlate data from cybersecurity tools, develop and automate dashboards in Power BI, and create custom scripts for data ingestion. You will also support data analysis, produce periodic reports, and implement API integrations to enhance data flow for security metrics visualization.
Featured Jobs
As a Data Engineer, you will design and implement database solutions, build robust data pipelines for AI model training, and monitor system performance. The role involves working with various databases and cloud services to ensure data quality and reliability.
As a Data Engineer at Capital Group, you will design and implement large-scale data architectures, optimize data processing systems on AWS, and work with complex data queries. Your role includes documenting system designs, collaborating with teams, and improving data ingestion frameworks.
As a Low-Latency Rust Data Engineer, you will develop and maintain high-performance data pipelines, integrate exchange data, and support trading teams with efficient data architecture in a fast-paced trading environment.
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The Data Engineer works with the Data & Analytics team to manage projects, analyze data issues, support internal queries, ensure compliance, and maintain documentation. They develop and manage data quality checks and assist in building data pipelines, requiring programming skills and knowledge of cloud platforms.
As a Data Engineer, you will design, build, and maintain data infrastructure for a clinical data registry, focusing on optimizing data pipelines and enabling insights to improve patient outcomes in healthcare. The role requires expertise in Big Data and cloud technologies.
The Principal Data Engineer will design and implement end-to-end data workflows for ML modeling, improve model performance, and enhance data processing frameworks. Responsibilities include creating standards and best practices, ensuring data accuracy, and collaborating with data scientists to meet data needs.
The Data Engineer role at Dynatron Software involves creating and managing data pipelines and ensuring data quality within the company's SaaS and DaaS products. Responsibilities include leading data architecture initiatives using Snowflake, developing ETL processes, collaborating with cross-functional teams, and addressing data quality issues.
The Cloud Data Engineer will develop and engineer solutions primarily using Python and Spark within AWS Glue, along with managing OpenSearch and DynamoDB. The role also involves programming with Neptune Graph Database, developing REST APIs, and constructing AWS infrastructure elements like IAM roles and policies.
As a Data Engineer, you will build and optimize production-grade data solutions on AWS or GCP, develop scalable ETL pipelines, and manage data storage and transformation routines. You will work closely with the Machine Learning and Data Platform team and engage with both technical and business stakeholders.
The Cloud Data Engineer will design and implement scalable data processing solutions using PySpark and AWS Big Data technologies, oversee the integration of Palantir, optimize AWS Cloud services, manage AWS Batch workflows, and mentor junior staff while ensuring data quality and compliance with industry standards.
The Lead AWS Data Engineer will design and implement scalable Big Data solutions using AWS services, oversee deployment and management of AWS EC2 instances, and develop Python scripts for data processing. Responsibilities include maintaining AWS EMR, implementing DevOps practices, and mentoring junior team members.
As a Principal Data Engineer at Lovelytics, you will design and implement data pipelines using Databricks, architect data lakes and warehouses, and ensure project milestones are met. You will also lead technical engagements, translate business requirements into solutions, and collaborate with teams to optimize data governance and security.
As an Intermediate Data Engineer, you will develop new product features and enhance existing products using ETL (Python + SQL), ETL Pipelines (Airflow), and API (Go) development. This role involves participating in the entire product lifecycle, ensuring the reliability and efficiency of data processing solutions.
The Data Engineer II will support integration, validation, enrichment, and aggregation of healthcare data. Responsibilities include designing data ingestion pipelines using Databricks on Azure, automating processes, implementing data lake architecture best practices, and working collaboratively to identify and acquire new data sources.
The Senior Data Engineer/Manager will lead the data strategy for Plasma-Derived Therapies, developing data models and ingestion pipelines while ensuring data quality for real-time decision making. Responsibilities include creating and maintaining data systems, collaborating with IT and business teams, and facilitating data-driven decision-making across the organization.
The Senior Data Engineer will apply data strategies to solve business problems, identify data sources, perform data transformations and integrations, and formulate technical solutions. They will utilize various database technologies, ETL techniques, and analytics methods to support data-driven decision-making in the organization.
As a Data Engineer III in the Data Ventures team, you will be responsible for data transformation and integration, data modeling, and code development. You will create data pipelines, perform quality checks, and model complex data relationships to support various business needs. The role also involves contributing to data governance and providing actionable insights to improve business processes.
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