A career in IBM Consulting is rooted by long-term relationships and close collaboration with clients across the globe. You'll work with visionaries across multiple industries to improve the hybrid cloud and AI journey for the most innovative and valuable companies in the world. Your ability to accelerate impact and make meaningful change for your clients is enabled by our strategic partner ecosystem and our robust technology platforms across the IBM portfolio; including Software and Red Hat. Curiosity and a constant quest for knowledge serve as the foundation to success in IBM Consulting. In your role, you'll be encouraged to challenge the norm, investigate ideas outside of your role, and come up with creative solutions resulting in ground breaking impact for a wide network of clients. Our culture of evolution and empathy centers on long-term career growth and development opportunities in an environment that embraces your unique skills and experience.
As a Senior Python Data Engineer, you will play a pivotal role in our organization. You will be responsible for designing, developing, and implementing robust data solutions using Python. This role demands a proactive, self-reliant individual with a passion for their work.
Key responsibilities include:
- Designing and building solutions to transfer data from various operational and external environments
- Creating and implementing Extract, Transform, and Load (ETL) processes, ensuring the seamless flow of data
- Writing high-quality, object-oriented code in Python, applying software design patterns in practice.
- Utilizing NumPy and Pandas for data manipulation and analysis.
- Applying software engineering best practices for Python( (linters, virtual environments, unit testing, static typing, etc.)
- Managing version control with git & GitHub (CLI).
- Collaborating with cross-functional teams to integrate data pipelines into our existing systems.
- Staying updated with the latest advancements in data engineering and data science fields.
- Extensive experience with Python, especially for data engineering tasks and using Docker for production-grade microservices.
- Strong Python skills for production microservices, such as Flask or FastAPI
- Demonstrated proficiency in Python for data engineering, including creating and managing ETL processes.
- Solid understanding of software engineering best practices for Python, such as linters, virtual environments, unit testing, static typing.
- Proven ability to effectively use NumPy and pandas for data manipulation and analysis.
- Strong experience in writing high-quality, object-oriented code in Python and applying software design patterns.
- Confident user of Git & GitHub (CLI).
- Excellent English language is a must
- Prior experience in any regulated industry, such as finance, healthcare, or government.
- Notable experience or certifications in AWS projects or services.