

Ingress IT Services
Databricks Machine Learning Engineering
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is a Databricks Machine Learning Engineer for a 12+ month contract in Plano, TX, offering a hybrid work model. Requires 10+ years in Data & Analytics, strong ML engineering skills, Azure Databricks experience, and proficiency in Python and SQL.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
560
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🗓️ - Date
June 2, 2026
🕒 - Duration
More than 6 months
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🏝️ - Location
Hybrid
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Plano, TX
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🧠 - Skills detailed
#Data Engineering #Automation #Delta Lake #Data Quality #Data Science #ML (Machine Learning) #Visualization #Microsoft Power BI #SQL (Structured Query Language) #Azure Databricks #Azure #Python #MLflow #BI (Business Intelligence) #Data Transformations #DAX #Strategy #Data Architecture #Scala #Leadership #Datasets #Semantic Models #Databricks #Predictive Modeling #"ETL (Extract #Transform #Load)" #Data Pipeline
Role description
Duration: 12+ month contract
Need 10+ years of experience
Machine Learning Engineering opportunity. Client is not open to one-dimensional Data Scientist.
Hybrid opportunity in Plano, TX 3 days onsite and 2 days remote
Strong communication and business acumen is required as stakeholders/directors/managers/engineers are all onsite
2nd round interview is onsite
Top Skills' Details
Leadership & Technical Expertise:
5–7 years of hands‑on ML engineering and data engineering experience, including building and hydrating curated data models and leading technical teams.
Proven ability to design ML‑ready data architectures and establish engineering standards, coding practices, and scalable workflows.
Deep understanding of Medallion Architecture, including how to ingest raw source data into Bronze, refine and validate it in Silver, and deliver clean, conformed, analytics‑ and ML‑ready Gold Layer datasets.
Azure Databricks:
Extensive experience using Azure Databricks for ML development, feature engineering, and data engineering pipelines.
Background migrating workloads to Databricks and leveraging Delta Lake, MLflow, and Databricks Workflows to operationalize ML and data transformations.
Python & SQL:
Strong proficiency in Python for model development, feature engineering, and MLOps automation.
Advanced SQL skills to build transformations, views, and optimized ELT pipelines that hydrate the Gold Layer.
Comfortable working in a fast‑paced, collaborative environment where experimentation and iteration are encouraged.
Data & Analytics Background:
10+ years in Data & Analytics, delivering enterprise‑scale data and ML solutions.
Experience designing feature stores, ML‑ready semantic layers, and production‑grade data assets.
Ability to integrate ML outputs into analytics tools and business‑facing dashboards.
Analytics & Visualization:
Experience designing semantic models and dashboards to surface ML insights, data quality metrics, and model performance.
Familiarity with Power BI best practices, including DAX and visualization standards.
Job Description
Overview:
We are seeking a Senior ML Engineer with strong data engineering foundations and deep experience building ML‑ready data pipelines within a Medallion Architecture. This role will lead technical initiatives, shape the ML and data engineering strategy, and help build a modern data platform that powers advanced analytics, predictive modeling, and enterprise‑scale machine learning.
You will design and implement scalable ML pipelines, ensure high‑quality data flows from ingestion to the Gold Layer, and collaborate across teams to deliver intelligent, data‑driven solutions.
Duration: 12+ month contract
Need 10+ years of experience
Machine Learning Engineering opportunity. Client is not open to one-dimensional Data Scientist.
Hybrid opportunity in Plano, TX 3 days onsite and 2 days remote
Strong communication and business acumen is required as stakeholders/directors/managers/engineers are all onsite
2nd round interview is onsite
Top Skills' Details
Leadership & Technical Expertise:
5–7 years of hands‑on ML engineering and data engineering experience, including building and hydrating curated data models and leading technical teams.
Proven ability to design ML‑ready data architectures and establish engineering standards, coding practices, and scalable workflows.
Deep understanding of Medallion Architecture, including how to ingest raw source data into Bronze, refine and validate it in Silver, and deliver clean, conformed, analytics‑ and ML‑ready Gold Layer datasets.
Azure Databricks:
Extensive experience using Azure Databricks for ML development, feature engineering, and data engineering pipelines.
Background migrating workloads to Databricks and leveraging Delta Lake, MLflow, and Databricks Workflows to operationalize ML and data transformations.
Python & SQL:
Strong proficiency in Python for model development, feature engineering, and MLOps automation.
Advanced SQL skills to build transformations, views, and optimized ELT pipelines that hydrate the Gold Layer.
Comfortable working in a fast‑paced, collaborative environment where experimentation and iteration are encouraged.
Data & Analytics Background:
10+ years in Data & Analytics, delivering enterprise‑scale data and ML solutions.
Experience designing feature stores, ML‑ready semantic layers, and production‑grade data assets.
Ability to integrate ML outputs into analytics tools and business‑facing dashboards.
Analytics & Visualization:
Experience designing semantic models and dashboards to surface ML insights, data quality metrics, and model performance.
Familiarity with Power BI best practices, including DAX and visualization standards.
Job Description
Overview:
We are seeking a Senior ML Engineer with strong data engineering foundations and deep experience building ML‑ready data pipelines within a Medallion Architecture. This role will lead technical initiatives, shape the ML and data engineering strategy, and help build a modern data platform that powers advanced analytics, predictive modeling, and enterprise‑scale machine learning.
You will design and implement scalable ML pipelines, ensure high‑quality data flows from ingestion to the Gold Layer, and collaborate across teams to deliver intelligent, data‑driven solutions.






