Senior Data Engineer, AI/ML

Jobtailor; Irving (TX); On-site; USD 120,000 - 170,000; Full time

Job summary

Wellfit is seeking a data engineer/AI professional in the US to drive hands-on AI/ML and data engineering, mining data, and productizing insights. You will train models for inference and anomaly detection, collaborating with tech and business leaders to translate data into tangible business impact.

You will work with Azure-centric tools (Fabric, Azure ML, data services) and translate knowledge from AWS/Databricks/Bedrock into Wellfit's Azure environment, delivering prototypes to production-scale

Qualifications

• 5+ years of professional experience in data engineering, analytics engineering, machine learning, AI/ML engineering, applied data science, or a related technical field.
• Strong hands-on experience working with business data, identifying patterns, and translating data into insights or solutions.
• Experience with AI/ML concepts including model training, inference, evaluation, and applied machine learning use cases.
• Strong technical foundation in data pipelines, data modeling, analytics, experimentation, and production-grade data solutions.
• Experience with modern cloud-based data and AI platforms.
• Preferred experience with Microsoft Fabric, Azure AI Foundry, Azure Machine Learning, Azure data services, or other Microsoft data/AI tools.
• Comparable experience with AWS, Databricks, Bedrock, Snowflake, or similar platforms is also valuable, especially if you can translate that knowledge into an Azure-centric environment.
• Ability to connect technical work to business value. You should be able to explain not just what you built, but why it mattered, what business problem it solved, and what impact it created.
• Strong communication skills with the ability to explain complex data findings clearly and practically.
• A builder mindset. This role requires someone who can work in the weeds, pull out the data, make sense of it, and help build something from the ground up.
• High initiative, intellectual curiosity, and the ability to operate without heavy hand-holding.
• Comfort working in a fast-moving, entrepreneurial environment where the opportunity is not simply to maintain existing reports, but to create new intelligence, products, and business value.

Responsibilities

• Own hands-on AI/ML and data engineering work focused on understanding, mining, and productizing Wellfit’s data.
• Train, evaluate, and apply models for inference, insight generation, anomaly detection, and business intelligence use cases.
• Partner with technology and business leaders to understand what the data is telling us, why it matters, and how it can be used to improve business outcomes.
• Identify anomalies, trends, correlations, and variances in performance across practices, products, transactions, demographics, service types, and customer behavior.
• Help uncover opportunities related to product performance, plan adoption, transaction volume, collections, fraud, customer growth, and other business-critical areas.
• Build data-driven solutions that can support consultative insights for customers, helping practices understand how to grow and keep their business healthy.
• Work with modern AI/data platforms, preferably within the Microsoft ecosystem, including Microsoft Fabric, Azure AI Foundry, Azure data services, and related tools.
• Translate experience from other modern data/AI ecosystems, such as AWS, Databricks, Bedrock, or similar platforms, into Wellfit’s Azure-centric environment.
• Develop prototypes, proof-of-concepts, and production-ready solutions that can scale beyond experimentation.
• Collaborate with engineering, product, data, operations, and executive stakeholders to turn raw data into usable intelligence.
• Communicate insights clearly to both technical and non-technical audiences, including the business problem, the data pattern, the recommendation, and the expected impact.
• Ask strong follow-up questions, challenge assumptions, identify gaps, and elevate the conversation rather than simply executing instructions.
• Bring high initiative, curiosity, and ownership to a greenfield-style opportunity where there is room to build, influence, and shape the future of AI and data at Wellfit.

Skills

Data engineering

Analytics engineering

Machine learning

AI/ML engineering

Applied data science

Cloud platforms

Tools

Microsoft Fabric

Azure AI Foundry

Azure Machine Learning

Azure data services

AWS

Databricks

Bedrock

Snowflake

Job description

Responsibilities

• Own hands‑on AI/ML and data engineering work focused on understanding, mining, and productizing Wellfit’s data.
• Train, evaluate, and apply models for inference, insight generation, anomaly detection, and business intelligence use cases.
• Partner with technology and business leaders to understand what the data is telling us, why it matters, and how it can be used to improve business outcomes.
• Identify anomalies, trends, correlations, and variances in performance across practices, products, transactions, demographics, service types, and customer behavior.
• Help uncover opportunities related to product performance, plan adoption, transaction volume, collections, fraud, customer growth, and other business‑critical areas.
• Build data‑driven solutions that can support consultative insights for customers, helping practices understand how to grow and keep their business healthy.
• Work with modern AI/data platforms, preferably within the Microsoft ecosystem, including Microsoft Fabric, Azure AI Foundry, Azure data services, and related tools.
• Translate experience from other modern data/AI ecosystems, such as AWS, Databricks, Bedrock, or similar platforms, into Wellfit’s Azure‑centric environment.
• Develop prototypes, proof‑of‑concepts, and production‑ready solutions that can scale beyond experimentation.
• Collaborate with engineering, product, data, operations, and executive stakeholders to turn raw data into usable intelligence.
• Communicate insights clearly to both technical and non‑technical audiences, including the business problem, the data pattern, the recommendation, and the expected impact.
• Ask strong follow‑up questions, challenge assumptions, identify gaps, and elevate the conversation rather than simply executing instructions.
• Bring high initiative, curiosity, and ownership to a greenfield‑style opportunity where there is room to build, influence, and shape the future of AI and data at Wellfit.

Requirements

• 5+ years of professional experience in data engineering, analytics engineering, machine learning, AI/ML engineering, applied data science, or a related technical field.
• Strong hands‑on experience working with business data, identifying patterns, and translating data into insights or solutions.
• Experience with AI/ML concepts including model training, inference, evaluation, and applied machine learning use cases.
• Strong technical foundation in data pipelines, data modeling, analytics, experimentation, and production‑grade data solutions.
• Experience with modern cloud‑based data and AI platforms.
• Preferred experience with Microsoft Fabric, Azure AI Foundry, Azure Machine Learning, Azure data services, or other Microsoft data/AI tools.
• Comparable experience with AWS, Databricks, Bedrock, Snowflake, or similar platforms is also valuable, especially if you can translate that knowledge into an Azure‑centric environment.
• Ability to connect technical work to business value. You should be able to explain not just what you built, but why it mattered, what business problem it solved, and what impact it created.
• Strong communication skills with the ability to explain complex data findings clearly and practically.
• A builder mindset. This role requires someone who can work in the weeds, pull out the data, make sense of it, and help build something from the ground up.
• High initiative, intellectual curiosity, and the ability to operate without heavy hand‑holding.
• Comfort working in a fast‑moving, entrepreneurial environment where the opportunity is not simply to maintain existing reports, but to create new intelligence, products, and business value.