Top Data Engineer Jobs
The Data Analyst/Engineer at PragerU will develop and maintain performance dashboards, optimize data systems for marketing campaigns, analyze data for improvements, and create reporting for analytics. This role requires collaboration with teams to enhance data-driven marketing initiatives and automate processes for efficiency.
The Data Developer will create a modern data platform, enhance data models, build scalable ETL pipelines, ensure data quality, and develop analytics tools in collaboration with various teams.
As a Data Engineer Consultant, the candidate will be responsible for designing and optimizing data infrastructure, creating scalable ETL processes, developing complex SQL queries, implementing dimensional models, and providing data visualization solutions. The role involves close collaboration with clients to ensure their data needs are met effectively.
The Data Engineer will leverage expertise in Informatica Cloud (IICS) for ETL processes, work with Oracle databases, SQL scripting, and Salesforce. The role demands strong analytical reasoning, problem-solving skills, and a solution-oriented mindset, with a requirement for in-person interviews and hybrid work.
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 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.
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.
Featured Jobs
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 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 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.
As a Staff Data Engineer, you will lead the design and implementation of large-scale data applications, manage complex integrations with various data sources, and enhance data architecture and performance. You will work collaboratively with engineering and business teams to influence data strategy and present data models, while also leading a small group of engineers in executing data projects.
As a Senior Data Engineer, you will lead small teams through complex projects, drive execution of business plans, and oversee engineering solutions from design to implementation. You will manage project timelines, ensure compliance, and promote innovation while enhancing designs to reduce defects.
As a Data Ops Engineer II at GEICO, you will design and build scalable data systems, ensure data quality, and engage in lifecycle collaboration to enhance services for users. You'll employ programming languages and cloud tools while driving process improvements and mentoring junior team members.
The Senior Java Data Engineer will design and build scalable systems to manage and transform large data sets, engage in software lifecycle collaboration, lead design sessions, mentor engineers, and improve engineering processes.
The Senior Data Engineer will design, develop, and maintain data pipelines and infrastructure, focusing on optimizing data for AI/ML models. Responsibilities include leading the creation of data warehouses, ensuring data quality, and collaborating with cross-functional teams to meet data requirements for machine learning applications.
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