Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Engineer with a contract length of "unknown," offering a pay rate of "unknown." Candidates must have at least 3 years of Power BI experience, relevant pharmaceutical industry knowledge, and certifications in Power BI Fabric, PL300, and Python.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
320
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🗓️ - Date discovered
June 5, 2025
🕒 - Project duration
Unknown
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🏝️ - Location type
On-site
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📄 - Contract type
W2 Contractor
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🔒 - Security clearance
Unknown
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📍 - Location detailed
Davie, FL
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🧠 - Skills detailed
#TensorFlow #Data Engineering #BI (Business Intelligence) #Data Science #Programming #Semantic Models #SQL (Structured Query Language) #Datasets #Visualization #Microsoft Power BI #Data Analysis #R #Python #Predictive Modeling #Computer Science #PyTorch #ML (Machine Learning)
Role description
Only W2 Candidates, PHARMACEUTICAL Industry experience is MUST HAVE for this role.
Data Engineer (Core Data Engineer role)
Shift: Monday - Friday 8:00 AM - 5:00 PM, 40 hours a week (100% Onsite)
Core Essential skill sets candidates must have:
1. Min 3 years experience as an expert using Power BI. Looking for persons who have created presentations and Dashboards. We are not looking for someone who has worked with a team to create these as a team but we are needing someone who knows how to create as aspects of the presentations and dashboard on their own.
1. Must be certified with Power BI Fabric.
1. Must have experience using Power BI creating models and dashboards. (Power BI fabrics & semantic models.)
1. Must have PL300 & Python certifications.
1. Must have experience using Power BI in Pharmaceutical Industry. (The worker must have good understanding of the Pharmaceutical industry.)
1. Proficiency in programming languages such as Python, R, and SQL. Experience with machine learning frameworks like TensorFlow or PyTorch.
Education:
Minimum Master's in Data Science and Computer Science - Graduate in recent years
Job Description:
a. Data Analysis: Analyze large datasets from manufacturing processes to derive actionable insights.
b. Predictive Modeling: Develop and implement predictive models to define process performance.
c. Collaboration: Work closely with cross-functional teams, including chemists, engineers, etc., to support data-driven decision-making.
d. Machine Learning: Apply machine learning algorithms to optimize process development and manufacturing processes.
e. Data Visualization: Create visualizations to communicate findings to stakeholders and support strategic planning.
Only W2 Candidates, PHARMACEUTICAL Industry experience is MUST HAVE for this role.
Data Engineer (Core Data Engineer role)
Shift: Monday - Friday 8:00 AM - 5:00 PM, 40 hours a week (100% Onsite)
Core Essential skill sets candidates must have:
1. Min 3 years experience as an expert using Power BI. Looking for persons who have created presentations and Dashboards. We are not looking for someone who has worked with a team to create these as a team but we are needing someone who knows how to create as aspects of the presentations and dashboard on their own.
1. Must be certified with Power BI Fabric.
1. Must have experience using Power BI creating models and dashboards. (Power BI fabrics & semantic models.)
1. Must have PL300 & Python certifications.
1. Must have experience using Power BI in Pharmaceutical Industry. (The worker must have good understanding of the Pharmaceutical industry.)
1. Proficiency in programming languages such as Python, R, and SQL. Experience with machine learning frameworks like TensorFlow or PyTorch.
Education:
Minimum Master's in Data Science and Computer Science - Graduate in recent years
Job Description:
a. Data Analysis: Analyze large datasets from manufacturing processes to derive actionable insights.
b. Predictive Modeling: Develop and implement predictive models to define process performance.
c. Collaboration: Work closely with cross-functional teams, including chemists, engineers, etc., to support data-driven decision-making.
d. Machine Learning: Apply machine learning algorithms to optimize process development and manufacturing processes.
e. Data Visualization: Create visualizations to communicate findings to stakeholders and support strategic planning.
