Top Data & Analytics Jobs

The Senior Data Engineer will create AWS-based data pipelines, ensuring data quality and a single source of truth while collaborating in an agile environment.

The Staff Data Engineer will lead financial data operations, ensuring accuracy and reliability of data pipelines, while collaborating with Finance, Product, and Engineering teams to enhance systems and decision-making processes.

The role involves building and owning data pipelines, maintaining data quality, and creating reporting systems that provide insights to various teams. The candidate will also design AI-ready data infrastructure.

As a Staff Data Engineer, you'll architect secure data systems, build pipelines, enforce best practices for sensitive data management, and mentor teams across Tonal.

The Lead Data Platform Engineer will design and build Virtuous's data platform, ensuring it is secure, scalable, and AI-ready. Responsibilities include architecting access controls, optimizing performance, and enabling self-service analytics while maintaining governance and compliance standards.

Design and build scalable cloud-native data platforms on AWS, architect streaming and batch ingestion pipelines, implement data lakes/warehouses, optimize data models, enforce security and governance, and expose curated datasets as APIs for applications.

The Senior Data Engineer will design and scale cloud-based data platforms, ensuring quality and performance while collaborating with cross-functional teams to deliver actionable data solutions.

Design, develop, and maintain large-scale data architectures and pipelines; deploy cloud-native data applications and CI/CD; support ML model productization; enforce code hygiene and best practices; mentor junior engineers; produce documentation and runbooks; collaborate with consulting teams and clients and travel as required.

Develop, maintain, and orchestrate cloud-native ETL/ELT pipelines using Python and Airflow. Build serverless workflows with AWS Lambda, model transformations with dbt, manage DynamoDB schemas, automate CI/CD, and implement data quality, testing, and governance to support analytics.

As a Data Engineer, you will architect and maintain the data systems, create pipelines and integrations, and ensure data quality for analytics and reporting.

The Cloud Data Engineer will design, implement, and manage data solutions on Microsoft Azure, create and maintain data pipelines, and ensure data security for decision-making processes.

Lead technical onboarding and integrations: map customer schemas to canonical models, design incremental and full data syncs, deploy pipelines across on-prem/cloud infra, collaborate with AI/ML teams to ensure high-fidelity inputs, and own successful customer deployments and last-mile onboarding.

Build and optimize core data platform: improve ClickHouse performance, create configurable ingestion schemas, develop shared Python libraries, design integration pipelines, and architect monitoring/observability for reliable, production-grade data delivery.

The Data Engineer will build and operationalize data solutions, design complex data systems, collaborate across teams, and ensure high-quality data management.

The Data Engineer II designs, develops, and maintains data integration and analytics solutions, ensuring data quality and accessibility for business stakeholders, while collaborating with teams to meet business needs.

The Data Engineer will design, develop, and implement data solutions, ensuring data integrity and availability, collaborating with stakeholders to meet business analytics needs.

Design, build, and operate GTM data pipelines, a unified data lake, and enrichment workflows using cloud data infra, LLMs, and orchestration tools to enable segmentation, ICP scoring, and revenue analytics.

Lead technical strategy for data architecture, build and optimize ETL/ELT and streaming pipelines, establish observability and data quality standards, mentor engineers, drive large-scale cross-team designs, and deliver self-serve data products for analytics and ML.

As a Senior Data Engineer, you will design and optimize data infrastructure for trading and risk analytics, mentor engineers, and ensure data quality and compliance in the energy sector.

The Data Integration Software Developer will integrate various data sources using Kafka, Elastic, and Databricks, managing deployments and developing automation solutions in an Agile environment.

Design and deliver data platforms and applications while optimizing pipelines and ensuring technical excellence through collaboration and leadership.

The Senior Data Engineer designs and maintains data pipelines, ensures data quality, and supports advanced analytics for U.S. Naval Aviation. They oversee data engineering practices and contribute to enterprise-scale architecture initiatives.

The Data Engineer will design and maintain data pipelines, collaborate with teams on data needs, and ensure data integrity and quality while leveraging AWS services.

The Data Engineer will build and maintain data pipelines, ensuring high-quality and scalable data systems while working on analytics and machine learning accessibility.

Lead and mentor multiple Databricks-focused data engineering teams, define engineering best practices and reusable frameworks, drive CI/CD and performance/cost optimization, build and support analytical and streaming pipelines, and collaborate with architects, product owners, and cross-functional partners to deliver high-quality data products.