Jobs at Lingaro

Designs and implements enterprise data architectures, governance frameworks, data models, integration pipelines, data platforms, and quality processes. The role uses Azure Synapse, Azure Data Factory, and Azure Data Lake, while optimizing databases, security, performance, and recovery. Responsibilities include stakeholder requirements gathering, data journey documentation, technology evaluation, data profiling and cleansing, technical guidance, and training. Requires strong communication, leadership, and at least six years of data and analytics experience.

Develop and maintain scalable AWS data engineering platforms and reusable Python modules. Build object-oriented data processing solutions, debug pipelines across Step Functions, Glue, Athena, and Lambda, and apply modern engineering practices including testing, CI/CD, and version control. Collaborate with agile teams to deliver reliable solutions across countries and business environments.

Lead and mentor a data engineering team while providing technical direction, troubleshooting support, and architectural guidance. Oversee scalable data solutions, data modeling, pipelines, quality assurance, coding standards, and performance optimization. Collaborate with stakeholders and project managers to deliver projects on schedule, manage risks, maintain documentation, and ensure security and regulatory compliance. Serve as a customer advisor and primary technical point of contact.

Designs scalable data architectures, models, pipelines, ETL frameworks, governance strategies, and cloud-based data solutions. Collaborates with stakeholders, data scientists, analysts, and engineering teams to translate business needs into technical implementations. Provides technical leadership and mentorship, oversees implementation, ensures data quality and security, optimizes performance, documents architecture, and supports project planning.

Design and implement Azure-based data processing systems, scalable data pipelines, data warehouses, data lakes, and ETL workflows. Transform and optimize structured and unstructured data, tune queries, improve storage and retrieval performance, and resolve system bottlenecks. Collaborate with data scientists, analysts, and stakeholders to deliver technical solutions while working within Agile methodologies.

Designs and oversees scalable GCP data architectures and infrastructure. Defines data models, schemas, pipelines, governance, security, and quality practices; selects and integrates data technologies; guides engineering teams; supports implementation, optimization, documentation, and project planning. Collaborates with stakeholders, analysts, and data scientists to translate business needs into reliable data engineering solutions.

Designs, builds, and supports GCP data ecosystems, including cloud storage, processing, warehouses, data lakes, pipelines, and integrations. Responsibilities include requirements gathering, data modeling, performance optimization, troubleshooting, monitoring, root cause analysis, and client collaboration. The role also mentors junior data engineers and contributes to ETL/ELT, orchestration, transformation, and database management initiatives.

Build enterprise AI agents using Microsoft Copilot Studio and Azure AI Foundry. Develop topics, triggers, routing, fallback handling, generative answers, RAG, knowledge grounding, citations, metadata-based retrieval, multilingual capabilities, and prompts. Integrate agents with Power Automate, SharePoint, Dataverse, Teams, Azure AI Search, and Azure OpenAI or Foundry models. Support troubleshooting, security, environments, ALM, and DEV/UAT/PROD deployments.

Lead business analysis for procurement-focused BI projects. Gather stakeholder requirements, document business processes, create functional specifications and data mappings, and define Power BI dashboards, data models, calculations, and visualizations. Support project planning, scope and milestone tracking, RAID and decision logs, governance communications, UAT, deployment, training, and hypercare. The role requires strong Power BI, data modeling, DAX, Azure, ETL/ELT, procurement analytics, and cross-functional stakeholder management experience.

Designs, builds, deploys, and optimizes cloud-based data pipelines on GCP. Integrates data from databases, APIs, and streaming platforms using ETL and ELT processes; manages BigQuery and NoSQL databases; performs data modeling and query optimization; and uses Airflow and modern transformation tools. Collaborates with data scientists, analysts, clients, and business stakeholders in distributed multinational teams.

Lead supply chain consulting engagements across presales, discovery, requirements analysis, solution design, and delivery. Bridge business stakeholders and technical teams to define functional requirements, perform fit-gap and process analysis, design data/AI-enabled supply chain solutions, support UAT, and drive stakeholder alignment and presales materials for transformation programs.

Develop and maintain scalable AWS data pipelines, modify Lambda functions and SQL processing jobs, design Iceberg-based data models, optimize Athena and Spark workloads, and implement data quality, observability, testing, governance, and documentation practices. The role also requires collaboration with engineering, product, and data stakeholders, along with GitLab-based version control and CI/CD or Infrastructure as Code familiarity.

Design, develop, and maintain Python backend services, RESTful APIs, and scalable microservices. Deploy and manage Azure cloud solutions, CI/CD pipelines, automated testing, Docker, and Kubernetes environments. Collaborate in Agile/Scrum teams through code reviews, planning, and architecture discussions. Apply database, data modeling, cloud architecture, scalability, security, and performance optimization knowledge, with potential work involving Databricks, Golang, React, infrastructure as code, and event-driven systems.

Designs and evolves an Azure-based observability and data quality platform. Builds reliable, automated infrastructure using IaC, CI/CD, Python, and Shell scripting; integrates AKS, Kafka, Databricks, Flink, Fivetran, and Azure SQL Server; develops monitoring and dashboards with Grafana, Prometheus, Power BI, or Databricks; applies SRE and FinOps practices to improve reliability, performance, data quality, incident response, compliance, and cloud cost efficiency.

Leads business analysis for procurement and finance analytics initiatives. Elicits and documents requirements, translates business needs into Power BI dashboard specifications, manages stakeholder alignment, supports project governance, and coordinates UAT, deployment, training, and post-go-live support. Mentors business analysts and drives improvements to analysis standards and delivery practices. Requires strong Power BI, data modeling, DAX, Azure analytics, procurement data, and bilingual English-Japanese communication skills.

Lead AI strategy, consulting, advisory, business development, presales, solution design, and client delivery. Identify high-value AI use cases, lead proof-of-concept initiatives, research emerging technologies, develop thought leadership, and support the launch and scaling of AI solutions. Balance strategic leadership with hands-on technical execution while collaborating with data scientists and AI architects to drive client AI adoption.

Lead supply chain business analysis and consulting across presales, RFPs, client discovery, requirements gathering, process mapping, fit-gap analysis, solution design, and implementation support. Translate business needs into functional requirements and scalable technology solutions using supply chain platforms, analytics, and AI. Facilitate stakeholder workshops, define KPIs and analytics requirements, support testing and deployment planning, and manage client relationships across business and technology teams.

The role involves shaping Data Management strategy, leading solutions development, driving AI innovation, building collaborations, and coaching junior team members.

Design, build, and maintain cloud-native backend services on Google Cloud using Python, FastAPI, SQLAlchemy, and PostgreSQL. Containerize with Docker, implement CI/CD via GitHub Actions, collaborate in GitHub, and optionally contribute to frontend work with TypeScript/Next.js.

Lead Data, Analytics, AI, and GenAI presales activities for strategic enterprise opportunities. Facilitate discovery workshops, translate business needs into scalable architectures, lead RFP and RFI responses, and present solutions to executives. Design end-to-end AI and cloud architectures across Azure, GCP, Databricks, and open-source ecosystems. Advise on AI transformation use cases, roadmaps, governance, and implementation, while mentoring delivery teams and developing reusable frameworks, offerings, thought leadership, and customer success materials.