Assembler for Boyd Thermal by Eaton, responsible for assembling parts per prints, inspecting, bonding, and testing components in a manufacturing environment.
Responsibilities
Assemble parts per prints and process instructions using necessary tooling
Perform basic math calculations and interpret basic blueprints
Conduct first piece inspection using visual or dimensional specifications
Perform accurate wanding and record keeping tasks
Apply bonding, pads, springs, pins, fans and other hardware per print using fixtures, tooling, hand and power tools
We are seeking a visionary and hands-on Enterprise Data Integration Architect to join our Integration Architecture team and serve as the dedicated integration representative to partner with the Data & AI organization. This role is pivotal in shaping and executing our enterprise-wide integration strategy for data and AI initiatives, leveraging cutting-edge technologies and cloud-native platforms on AWS and/or Azure.
Responsibilities
Define and drive the integration strategy for data and AI initiatives across the enterprise
Partner with Data & AI leadership to align integration architecture with business goals and data strategies
Evaluate and recommend modern integration technologies and patterns (e.g., event-driven, API-led, streaming, data mesh)
Partner with regional teams in defining and designing integration patterns and architectures
Design scalable, secure, and resilient integration architectures on AWS and/or Azure using services such as Glue, Lambda, Kinesis, S3, Redshift, and others
Requirements
Bachelor’s or Master’s degree in Computer Science
Information Systems, or related field
Nice to have: Azure cloud services
Nice to have: regulated industries (healthcare, finance)
Lead technical resources for data engineering, automation, dashboards, and reporting workflows in alternative investment strategies.
Locations (2)
Hyderabad, Telangana, India
Los Angeles, California, United States
Responsibilities
Design and maintain cloud-ready data pipelines and dimensional models using SQL, Python, Power BI, Microsoft Fabric / Azure, and AWS services
Implement secure, automated ingestion from Oaktree systems, MDM, data warehouse sources, FTP/email feeds, vendor files, Salesforce, servicer or administrator reports, and governed reporting datasets
Build performant ELT/ETL workflows for investment, portfolio, cash activity, audit log, exception, exposure, attribution, and reporting-control data
Develop reusable SQL and Python utilities, including advanced SQL optimization, window functions, pandas/PySpark data engineering, REST/GraphQL integration, validation checks, and test automation
Create institutional Power BI dashboards, semantic models, paginated reports, DAX measures, Power Query/M transformations, row-level security, and deployment pipeline assets
Build and scale production-grade AI solutions on AWS for insurance platforms
Compensation
$120,000 - $150,000 annual base salary depending on experience, qualifications, and geographic location $130,000 - $170,000 annual base salary depending on experience, qualifications, and geographic location in CA, CT, MA, NJ, NY, and PA
Responsibilities
Build AI systems
Design and implement end-to-end AI/ML solutions including LLM-based applications
Build RAG pipelines using vector databases and enterprise data sources
Build machine learning models that automate their training, validation, monitoring, and retraining
Develop APIs and services to operationalize AI capabilities across the organization
As an AI Engineer on the platform side, you will build and operate the infrastructure that makes AI applications reliable in production: the data pipelines that feed them, the embedding and retrieval layers behind them, and the services, APIs, and monitoring around them.
Compensation
EUR 60,000–70,000 per annum
Responsibilities
Design, build, and operate the pipelines that power AI applications: document and data ingestion, chunking and embedding pipelines, vector stores, and retrieval services.
Productionize LLM-powered applications as reliable services: APIs, containerised deployments, observability, cost monitoring, and access control.
Integrate AI workloads with the data lakehouse platform — streaming (Kafka) and batch sources, query layers, and time-series stores.
Build and maintain evaluation, logging, and feedback infrastructure for AI applications in production.
Contribute to core data engineering duties: developing and maintaining data pipelines, ensuring data quality and reliability, and improving platform performance and efficiency.
Staff-level role focused on leading design and evolution of modern data platform architecture, implementing advanced architectural patterns, and managing enterprise-scale distributed systems infrastructure.
Design, build, and own highly scalable data pipelines and data infrastructure for Partnerize’s AI-driven products.
Responsibilities
Design, build, and own highly scalable data pipelines and data infrastructure
Process and analyze large-scale datasets from multiple digital sources and environments
Build reliable infrastructure and reusable components that enable Data Scientists and Product teams to develop and productionize data-driven capabilities
Design data architectures optimized for scalability, reliability, performance, and cost
Develop production-grade data processing systems handling high volumes of structured and unstructured data
AI Automation & Innovation Analyst focused on full‑stack development, data integration, and AI‑enabled workflows for Sony Pictures Entertainment’s LATAM Data Analytics & Business Insights team.
Locations (2)
Bogota, Colombia
Buenos Aires, Argentina
Responsibilities
Develop and implement automation solutions that streamline repetitive, manual, or time‑consuming business processes
Build AI‑enabled workflows using Python, APIs, workflow automation tools, and cloud‑based data assets
Design and build end‑to‑end solutions including data ingestion, backend logic, APIs, user interfaces, dashboards, lightweight web applications, internal tools, and deployment‑ready prototypes
Work hands‑on with the company’s AWS‑based data warehouse to query, transform, integrate, and prepare data for AI, automation, and business‑facing solutions
Partner with Analytics and Data Science teams to understand analytical assets, predictive models, business logic, reporting products, and strategic priorities
Bachelor's or Master's degree in Computer Science, Data Science, Data Analytics, Engineering, Statistics, Mathematics, Finance, Accounting or a related analytical field, or equivalent deep work experience building data/BI solutions in investment management
the salary range for this role is $173,000.00 - $216,000.00 + target bonus.
Responsibilities
Lead the design and evolution of our modern data platform architecture, ensuring it remains scalable, available, and performant.
Apply in-depth knowledge of advanced architectural patterns—such as Event Driven, CQRS, event sourcing, and Saga patterns—to solve complex data challenges.
Develop, document, and communicate standard methods and processes to be utilized within our technology stack, including dbt, Airflow, Snowflake, Kafka, and traditional ETL.
Act as a key partner to senior leadership on strategic data projects and build strong working relationships with other IT leaders by providing technical acumen and thought leadership.
Architect and manage enterprise-scale data platforms while setting best practices for development teams, including security, privacy, monitoring & alerting, and CI/CD.
Bachelor’s or advanced degree in Computer Science, Data Science, Engineering, Information Systems, Statistics, Business Analytics, or a related quantitative or technical field
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