Senior Data Engineer
Design and operate AWS cloud infrastructure and data pipelines to support AI-powered financial systems. Lead technical discovery sessions with clients to translate business needs into automated AI agent workflows.
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Design and operate AWS cloud infrastructure and data pipelines to support AI-powered financial systems. Lead technical discovery sessions with clients to translate business needs into automated AI agent workflows.
Design, build, and maintain scalable data architectures, models, and ETL pipelines to ensure data integrity and performance. Collaborate with cross-functional teams to deliver data-driven insights and establish department-wide engineering procedures.
Design and operationalize automated systems for demand capture, lead routing, and GTM experimentation using AI and event-driven tools. Transform marketing workflows into production-grade systems to scale organic and inbound demand.
Design and maintain scalable PySpark-based data pipelines and Delta Lake tables on AWS to support federal clients. Collaborate with architects to implement secure, cloud-native data solutions and optimize pipeline performance and cost.
Architect and build a greenfield, multi-layer data warehouse and semantic layer to separate analytical workloads from production traffic. Establish data governance, tenant isolation, and traceability between structured records and unstructured drone imagery.
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The role serves as the analytics and forecasting expert for the Alternatives and Non-Core portfolio, translating data into actionable insights for strategic asset allocation and executive decision-making. Key duties include maintaining cash flow and NAV models, developing Power BI dashboards, and providing performance attribution and risk reporting.
Act as the senior analytical partner to the Marketing organization to define performance metrics and influence investment decisions. You will build the data foundations for AI capabilities and provide strategic recommendations across Growth, Corporate Marketing, and Revenue Operations.
Lead the planning, delivery, and governance of diverse data and AI projects while serving as the primary client-facing lead. Act as a trusted advisor to stakeholders from data owners to C-level executives to drive business value.
Design and maintain a compliant application data repository and integration architecture for web and mobile applications. Collaborate with stakeholders to optimize data delivery, automate manual processes, and oversee third-party engineering work.
Design, build, and launch scalable data pipelines to integrate customer databases and financial datasets. Monitor pipeline reliability and translate business requirements into analytical data flows that provide business value.
Drive data-driven decisions for critical business initiatives by leveraging machine learning and complex data analysis. Lead the design and execution of A/B experiments to optimize user acquisition and operational efficiency.
Design and maintain scalable data quality frameworks to ensure the accuracy and consistency of enterprise data across multiple domains. Implement automated checks within ETL pipelines and validate Power BI reports using AI-assisted practices and AIOps observability.
Design and implement a global, AI-first Customer Success function focusing on productivity, insights, and best practices. Lead data analytics for retention and growth while acting as a Technical Project Manager for strategic initiatives across multiple markets.
Design and implement a centralized data platform to create a Single Source of Truth for strategic company metrics. Collaborate with Product Engineering to evolve reporting capabilities and enable Business Intelligence integrations for clients.
Design and optimize enterprise-scale data solutions and reusable workflows within Snowflake and Azure environments. Build scalable ETL pipelines and implement data governance and compliance policies to ensure data quality.
The Database Developer is responsible for designing, building, and maintaining data systems and engineering pipelines across AWS and Azure environments. This includes implementing CI/CD practices, developing serverless functions, and optimizing data processing and monitoring.
Design and optimize PySpark/EMR pipelines and manage a Hudi-based medallion lakehouse on AWS. Own the end-to-end data platform reliability, cloud cost efficiency, and the deployment of data-serving APIs.
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Design, build, and maintain scalable data pipelines and ingestion processes to ensure data quality and reliability across enterprise platforms. Support the development of modern data architecture and automate processes to improve operational efficiency for internal and external stakeholders.
Design, develop, and deploy scalable data pipelines and ETL/ELT processes using the Dataiku DSS platform. Support a large-scale enterprise data lakehouse migration while collaborating with international business and technical stakeholders.
Build and maintain end-to-end data pipelines and create AI-ready analytical datasets. Collaborate with stakeholders to incorporate business logic and optimize pipelines for reliability and performance.
Provide L3 engineering support for Palantir Foundry and Foundation environments, focusing on resolving complex technical issues and software defects. Maintain production pipelines, platform workflows, and contribute to platform governance and stability.
The role involves leading the development and maintenance of data services and solutions to support products, downstream services, or infrastructure tools used across BEES. This includes designing efficient data models and implementing architectural improvements to enhance performance, monitoring, and evolution of data products.
The Senior Solutions Architect will provide technical leadership post-sales to guide strategic customers in designing and implementing big data projects, from architectural design to data engineering and model deployment. This role involves architecting production-level workloads, performance testing, optimization, and delivering training sessions to promote community adoption.
The Tech Lead will own the design, building, and delivery of high-quality AI/ML solutions, with a strong emphasis on Generative AI and LLMs. This involves hands-on development, technical leadership, and mentoring AI engineers on best practices across AI engineering and MLOps.
The Senior Data Engineer will be pivotal in building a robust data platform using Databricks to support skilled data professionals analyzing and improving a highly visible online product. Responsibilities include architecting and building scalable data platforms in AWS and Databricks, designing data pipelines, and optimizing infrastructure.
Design and implement core platform services exposed through high-quality APIs and SDKs for a unified data and AI/ML model development platform. Partner closely with AI/ML researchers, data engineers, and product teams to deliver a paved-path developer experience.
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The AWS Engineer will design, build, and maintain scalable data pipelines and analytics platforms on AWS. This includes transforming raw data into analytics-ready datasets and ensuring data quality and compliance.
Design, build, and maintain scalable data pipelines that support analytics and reporting. Collaborate with cross-functional teams to define data requirements and deliver actionable insights.
Responsibilities include presenting and analyzing data using charts, tables, and Excel, alongside interpreting financial reports and market performance to derive investor-focused takeaways. Analysts will also interpret factors like yield, price, and risk for asset merits and conduct deep quantitative risk modeling.
As a Senior Data Engineer, you will deliver on complex projects, either individually or by leading small teams. You will manage customer relationships and support pre-sales processes while mentoring junior engineers.
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