Intermediate Data Engineer
Job Description
Your Impact
As an Intermediate Data Engineer, you'll leverage engineering frameworks and best practices to design and construct essential data frameworks supporting our client service teams. Your efforts will enable software capabilities that assist data engineers, data scientists, consulting teams, and external clients alike, promoting innovation and efficiency across various domains.
In this role, you'll:
• Develop robust, scalable, and reproducible data pipelines for machine learning.
• Curate and prepare data for advanced model development.
• Manage secure data environments and contribute to research and development projects.
• Support the shift towards asset-based consulting, enhancing our entrepreneurial culture in the Chemicals practice.
• Collaborate within cross-functional Agile teams alongside experts in data science and machine learning.
Your work will positively influence complex, high-stakes projects, helping clients leverage data to meet their objectives and deliver enduring value. You will be part of our advanced analytics and data engineering community, with the potential to innovate and grow as a technology leader.
Your Growth
Our culture emphasizes continuous learning and development, providing structured programs to accelerate your transformation into a strong leader. You'll receive coaching and mentorship from colleagues at all levels while making an impact through innovative solutions.
• Continuous Learning: Engage in a feedback-rich environment designed to nurture your growth.
• A Voice That Matters: Your ideas and contributions will be valued from day one, fostering practical solutions.
• Global Community: Work within a diverse team spanning over 65 countries, enhancing creativity and problem-solving.
• World-class Benefits: Enjoy a comprehensive benefits package tailored to support your and your family's wellbeing.
Your Qualifications and Skills
• A degree in a quantitative field such as computer science or applied statistics, or equivalent experience.
• 2-5+ years of relevant experience.
• Proven ability in constructing data pipelines for advanced analytics.
• Experience handling structured, semi-structured, and unstructured data.
• Familiarity with distributed computing, cloud platforms, and analytics tools.
• Exposure to software engineering methodologies, including DevOps and MLOps.
• Proficient with technologies such as Python, PySpark, SQL, Airflow, Databricks, and cloud solutions like AWS and Azure.
• Exceptional time management skills in a complex, autonomous environment.
• Strong verbal and written communication skills in English and local languages.
If you're ready to take the next step in your career and contribute to impactful projects, we encourage you to apply!
Base location for this role is in Houston, Texas.
McKinsey & Company values diversity and is an Equal Opportunity employer. Qualified applicants will receive consideration for employment without regard to sex, gender identity, race, or any other characteristic protected by law.
