About the Role

We are looking for an experienced Data Delivery Lead to lead the delivery of a modern data platform for a strategic enterprise client, as part of one of our early and high-priority data transformation initiatives. The project is building on an initial phase that established the target architecture, delivery approach, and proof of concept. The next phase is focused on turning that foundation into a scalable, production-ready data platform using Microsoft Azure, with Microsoft Fabric at its core. As Data Delivery Lead, you will take ownership of the data workstream from planning through delivery. You will lead the data engineering team, work closely with project and architecture leads, and ensure that the platform is delivered to a high technical and delivery standard. This role is ideal for someone who combines strong data engineering experience with the ability to lead technical delivery and work confidently with both technical and business stakeholders.

What You'll Do

● Lead the delivery of the data platform workstream, from planning throughproduction.

● Translate the existing architecture and roadmap into clear technical deliverables and priorities.

● Lead and support the team throughout the delivery.

● Design and oversee data ingestion, transformation, modelling, and data quality activities.

About the Job

Join Excelya, where Audacity, Care, and Energy define who we are and how we work. We believe in creating bold solutions and fostering an inclusive environment where collaboration and individual growth go hand in hand. This role is an exciting managerial opportunity to contribute to Excelya’s Quality Assurance team.

In this hands-on and highly autonomous operational position, you will lead your team while actively shaping the organization’s quality culture. You will collaborate across functions and oversee critical QA processes, including vendor management, audits, CAPAs, and continuous improvement initiatives. This position offers a dynamic career path within a stimulating and expanding QA environment.

Key Responsibilities

In this role you are expected to:

Tiger Analytics is looking for experienced Machine Learning Engineers to join our fast-growing advanced analytics consulting firm. Our employees bring deep expertise in Machine Learning, Data Science, and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner.

We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world. You will be responsible for:

• Providing solutions for the deployment, execution, validation, monitoring, and improvement of data science solutions
• Creating Scalable Machine Learning systems that are highly performant
• Building reusable production data pipelines for implemented machine learning models
• Writing production-quality code and libraries that can be packaged as containers, installed and deployed

You will collaborate with cross-functional teams and business partners and will have the opportunity to drive current and future strategy by leveraging your analytical skills as you ensure business value and communicate the results.

Requirements

Tiger Analytics is looking for experienced Machine Learning Engineers to join our fast-growing advanced analytics consulting firm. Our employees bring deep expertise in Machine Learning, Data Science, and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner.

We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world. You will be responsible for:

• ML Engineer with 5-7 years of IT experience.
• Pipeline Training Models, Building, Deployment, Testing, and Monitoring using AWS SageMaker, AWS CFT, AWS CodePipeline, Lambda, etc.
• Develop Airflow DAGs to run training and scoring pipelines
• Develop a Testing framework with Pytest
• Implement monitoring solution with homebrew solution using Lambda and Dash
• Develop Data Quality solutions potentially leveraging Great Expectations.

Requirements

Tiger Analytics is an advanced analytics consulting firm. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our consultants bring deep expertise in Data Science, Machine Learning, and AI. Our business value and leadership have been recognized by various market research firms, including Forrester and Gartner.

We are looking for a motivated and passionate Machine Learning Engineers for our team.

As part of this job, you will be responsible for:

• Providing solutions for the deployment, execution, validation, monitoring, and improvement of data science solutions
• Creating Scalable Machine Learning systems that are highly performant
• Building reusable production data pipelines for implemented machine learning models
• Writing production-quality code and libraries that can be packaged as containers, installed and deployed

Requirements