Top Data & Analytics Jobs

Design and own the companys end-to-end data and analytics stack: build metrics, dashboards, and reporting; instrument product and GTM signals; transform messy data into structured inputs for AI agents; and define analytics infrastructure (dbt, Snowflake, Mode) while partnering across founders, engineering, and GTM teams.

The role involves structuring and ingesting customer data, setting up ETL pipelines, and providing solutions for data export and import.

The Principal Data Engineer will lead data architecture initiatives, design scalable data systems, and oversee data standards across teams while ensuring high-quality data infrastructure and guiding engineering teams.

Lead implementation of ETL patterns and reliable data infrastructure, partner with business and engineering teams to prioritize and deliver integrations, APIs, and reusable components, and support operational data applications in an Agile environment.

As a Business Intelligence/Data Engineer, you will analyze data structures, implement data warehousing solutions, and design data visualizations while working with AI/ML services in cloud environments.

The Data Engineer will design and implement scalable data platforms, build data pipelines, collaborate with teams to ensure data quality, and streamline processes using AWS services and big data technologies.

Leads the design, implementation, and optimization of cloud-native data infrastructure, platforms, storage solutions, and complex data pipelines. Establishes engineering standards for testing, monitoring, releases, and reliability; troubleshoots cross-system failures and leads incident reviews. Partners with infrastructure, laboratory IT, data science, bioinformatics, and scientific teams to deliver secure, scalable solutions. Mentors engineers, guides technical initiatives, and uses generative AI to accelerate development and data transformation.

Build scalable data solutions and reconciliations to automate Compliance & Finance regulatory processes. Partner with stakeholders to translate requirements into designs, lead technical development, review code, and evolve standards for data pipelines and reporting.

Leads architecture, optimization, scaling, and ownership of Zoox’s enterprise and AI data platform. Builds self-healing pipelines, governance frameworks, data quality and observability systems, secure access controls, lifecycle policies, and automated CI/CD deployment infrastructure. Optimizes Databricks and AWS EMR performance and costs while enabling low-latency, AI-ready data foundations. The role also drives enterprise security, compliance, schema evolution, and developer velocity, with opportunities to apply GenAI, Terraform, and EKS.

Design and implement a financial knowledge graph architecture, build graph ingestion and transformation pipelines, apply graph algorithms and analytics, define best practices, drive adoption across teams, and mentor/hire engineers to scale the platform while collaborating with investment and compliance stakeholders.

Build and operate large-scale data ingestion pipelines powering research and trading platforms. Own pipeline quality, reliability, performance, and data health; collaborate with traders, quantitative researchers, and data owners; optimize compute, storage, and SLAs; migrate pipelines to modern platforms; and implement tools to detect and resolve source-data quality issues.

Design, build, and operate Databricks Lakehouse pipelines and Delta tables. Optimize Spark/SQL workloads, implement incremental/CDC patterns, ensure data quality, deliver documented datasets and dashboards (Power BI), and collaborate with stakeholders to meet SLAs while supporting data-driven decisions.

The candidate will improve the data ETL pipeline, build analytical tools, manage operations, and expand into new markets and asset classes.

Build and operate ingestion and transformation pipelines to turn messy insurance data into clean datasets. Design bronze/silver/fact layers, model and tune Postgres and analytical stores, define KPIs and reconciliation checks, orchestrate observable data jobs, and ensure end-to-end data quality for analytics and AI products.

The Data Engineer will design and manage data pipelines, develop datasets for product metrics, and collaborate with teams to ensure robust data integration and processing.

Lead architecture, systems, and roadmap for Coinbase's Compliance Reporting Data Platform. Design and build production-grade data models, pipelines, quality frameworks, validations, and certification processes. Establish data contracts, monitoring, reconciliation, and audit-ready processes. Partner with engineering and compliance stakeholders, respond to regulatory exams, and mentor engineers while shaping standards and documentation.

Design, build, and maintain ETL pipelines and big-data workflows from ingestion to consumption. Troubleshoot data/system issues, work in an agile team, handle structured/unstructured data and security logs, and support government data acquisition and sharing while meeting quality assurance and testing standards.

Lead design and implementation of a scalable Big Data Audience Management platform (500+ TB). Own data pipelines (ingest, validation, transformation, storage) using Spark and Scala, mentor engineers, perform R&D on new technologies, and partner with product managers to meet roadmap and business needs.

Senior ETL Data Developer to design, build, test, and support Epic Clarity and enterprise ETL solutions using SSIS (and DataStage). Develop and optimize ETL workflows, implement standards, troubleshoot complex integration issues, document designs, and collaborate with reporting, analytics, and business teams to deliver data warehouse solutions and integrations.

Design, implement, and maintain scalable data infrastructure and real-time processing for analytics platforms. Migrate systems from AWS to on-prem Kafka/Spark, implement data transformations, support production, optimize pipelines, query and analyze data, and build scripts and APIs to operationalize data science work.

Design, develop, and maintain Power BI BI solutions: build data models, create reports and dashboards, write DAX and Power Query transformations, query and integrate data with SQL, apply data warehousing/ETL principles, optimize performance, document solutions, troubleshoot issues, and collaborate with stakeholders.

The Data Engineer will support Data Analytics and Business Intelligence efforts, developing data pipelines, ensuring data performance, and collaborating within Agile frameworks to meet complex requirements for federal clients.

The Data Engineer will develop data pipelines, support data automation, collaborate with Agile teams, and ensure data reliability and performance. The role requires strong ETL skills and experience with relational databases, big data analysis, and CI/CD practices.

The Data Engineer will develop data pipelines, manage complex data sets, and ensure data reliability while collaborating within an Agile/Scrum team.

The Data Engineer will develop data pipelines, support Agile team collaboration, ensure data extraction performance, and promote process automation.