Data Engineer

Apply now: Data Engineer (R&D) , location is Remote . The start date is mid-April for this 6-month contract position.

Job Title: Data Engineer

Location: 100% Remote

Start Date Is: Mid-April

Duration: 6-month contract

Compensation Range: : $60-75/hr on W2 ONLY!

Benefits: This position is eligible for medical, dental, vision,
and 401(k).

Job Description:

This role will lead digital transformation initiatives focused on modernizing and structuring R&D data to support analytics, automation, and AI-driven innovation.

Day-to-Day Responsibilities:

• Work closely with R&D scientists, researchers, and IT teams to gather requirements and translate technical needs into actionable workflows

• Support data modernization initiatives by helping migrate data from legacy platforms to modern systems

• Partner with data engineers to structure, standardize, and manage R&D data sources

• Coordinate data workflows involving Python, Microsoft tools, and cloud platforms

• Facilitate communication between technical teams and scientific users to ensure solutions meet research needs

• Assist with automation and data integration projects across research environments

• Support reporting and data visualization efforts using tools such as Power BI

• Identify opportunities to improve data accessibility and streamline research processes

Requirements:

Must-Haves:

• 3 years of hands-on experience working within an R&D environment

• Experience supporting data engineering or data management projects

• Strong experience with Python and working with Python-based data workflows

• Experience handling Excel-based datasets and transferring data into structured systems

• Familiarity with Microsoft data ecosystem tools

• Experience with Databricks

• Exposure to Power BI or PowerApps

• Experience with automation and data workflow processes

• Strong communication skills with the ability to translate technical requirements between scientists and IT teams

• Familiarity with LIMS or Electronic Lab Notebook (ELN) systems

Nice-to-Haves:

• Experience with Oracle databases

• Strong SQL skills

• Experience working in scientific, chemical, or research organizations

• Exposure to AI-enabled data environments