Data Engineer

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Engineer in Davie, FL, for 12 months at $40.00/hr. Required skills include Power BI Fabric Certification, pharmaceutical industry experience, PL300, Python certifications, and proficiency in Python, R, and SQL. Master's or PhD in Data Science preferred.
🌎 - Country
United States
💱 - Currency
$ USD
💰 - Day rate
Unknown
Unknown
320
🗓️ - Date discovered
May 15, 2025
🕒 - Project duration
More than 6 months
🏝️ - Location type
On-site
📄 - Contract type
W2 Contractor
🔒 - Security clearance
Unknown
📍 - Location detailed
Davie, FL
🧠 - Skills detailed
#ML (Machine Learning) #Data Analysis #BI (Business Intelligence) #Data Engineering #SQL (Structured Query Language) #TensorFlow #Datasets #Microsoft Power BI #Python #Semantic Models #Visualization #Data Science #Programming #R #PyTorch
Role description
Job Title: Data Engineer (Core Data Engineer role) Location: Davie, FL 33314 Duration: 12 months Pay Range: $40.00/hr on W2 Shift: Monday - Friday 8:00 am - 5:00 pm, 40 hours a week Core Essential skill sets candidates must have: • Must have Power BI Fabric Certification. • Must have experience using Power BI creating models and dashboards. (Power BI fabrics & semantic models.) • Must have PL300 & Python certifications. • Must have experience using Power BI in the Pharmaceutical Industry. (The worker must have a good understanding of the pharmaceutical industry.) • Proficiency in programming languages such as Python, R, and SQL. Experience with machine learning frameworks like TensorFlow or PyTorch. Education: • Master's or PhD in Data Science - College fresh or with one year experience in pharmaceutical experience using Power BI. Screenings: • Basic Background • Drug -11-panel w/Fentanyl • Medical Screenings: • Vision Screen - Near, Far, Color, Depth and Peripheral • Spirometry & OSHA Respirator Questionnaire Job Description: • Data Analysis: Analyze large datasets from manufacturing processes to derive actionable insights. • Predictive Modelling: Develop and implement predictive models to define process performance. • Collaboration: Work closely with cross-functional teams, including chemists, engineers, etc., to support data-driven decision-making. • Machine Learning: Apply machine learning algorithms to optimize process development and manufacturing processes. • Data Visualization: Create visualizations to communicate findings to stakeholders and support strategic planning.