Data Engineer

Client Description: Fully remote, EST hours Our client, a leading healthcare provider, is seeking a talented Data Engineer to join their dynamic team and contribute to their mission of delivering exceptional healthcare services. We can facilitate w2 and corp-to-corp consultants. For our w2 consultants, we offer a great benefits package that includes Medical, Dental, and Vision benefits, 401k with company matching, and life insurance. Rate: $55.00 to $60.00/hr. w2 Responsibilities: • Collaborate with cross-functional teams to develop and implement data-driven solutions that support financial planning and analysis (FP&A) initiatives. • Utilize your expertise in data engineering to design, build, and maintain scalable data pipelines using tools such as Databricks, PySpark, and Python. • Conduct experiments and leverage artificial intelligence to uncover data insights that drive strategic decision-making. • Apply critical thinking skills to break down complex problems into manageable components and develop effective solutions. • Work independently in a fast-paced environment, demonstrating a self-starter attitude and the ability to thrive in ambiguity. • Engage in a thin slice approach to project management, focusing on delivering incremental value without relying on traditional PI planning or Agile methodologies. Qualifications: • At least 2-3 years of experience in data engineering, data science, or machine learning, with a strong background in Python programming. • Proven understanding of finance, accounting, and FP&A processes, preferably within the finance or insurance industry. • Experience with data engineering tools and platforms, including Databricks and PySpark. • Demonstrated ability to conduct experiments and apply AI techniques to extract meaningful insights from data. • Strong problem-solving skills, with the ability to articulate your thought process and approach to breaking down complex problems. • Eagerness to learn and adapt to new technologies and methodologies in a rapidly evolving field. Education: • Bachelor's degree in Computer Science, Data Science, Engineering, Finance, or a related field. Advanced degrees or relevant certifications are a plus.