Data Engineer II - McKinsey Transformatics
Indexed description
In return for your drive, determination, and curiosity, we'll provide the resources, mentorship, and opportunities you need to become a stronger leader faster than you ever thought possible. Your colleagues—at all levels—will invest deeply in your development, just as much as they invest in delivering exceptional results for clients. Every day, you'll receive apprenticeship, coaching, and exposure that will accelerate your growth in ways you won’t find anywhere else.
When you join us, you will have:
- Continuous learning: Our learning and apprenticeship culture, backed by structured programs, is all about helping you grow while creating an environment where feedback is clear, actionable, and focused on your development. The real magic happens when you take the input from others to heart and embrace the fast-paced learning experience, owning your journey.
- A voice that matters: From day one, we value your ideas and contributions. You’ll make a tangible impact by offering innovative ideas and practical solutions, all while upholding our unwavering commitment to ethics and integrity. We not only encourage diverse perspectives, but they are critical in driving us toward the best possible outcomes.
- Global community: With colleagues across 65+ countries and over 100 different nationalities, our firm’s diversity fuels creativity and helps us come up with the best solutions for our clients. Plus, you’ll have the opportunity to learn from exceptional colleagues with diverse backgrounds and experiences.
- World-class benefits: On top of a competitive salary (based on your location, experience, and skills), we provide a comprehensive benefits package to enable holistic well-being for you and your family.
Our Transformatics team builds data and AI products to provide analytics insights to clients and McKinsey teams involved in transformation programs across the globe. The current team is composed of data engineers, data scientists and project managers who are spread across several geographies. The team covers a variety of industries, functions, analytics methodologies and platforms – e.g. Cloud data engineering, advanced statistics, machine learning, predictive analytics, MLOps and generative AI.
As a member of the team, you will work alongside a team of skilled data engineers to design, build, and optimize scalable data solutions that power analytics, reporting, and machine learning. As a data engineer, you will be responsible for procuring data from APIs, ingesting it into the data storage layer, and ensuring its quality through cleaning and standardization. You will develop scalable data ingestion pipelines that integrate on cloud ecosystems, making data readily available for analytics and reporting.
You will also be part of an effort to build next-gen data platforms on the cloud to enable our business stakeholders to have rapid data access and incubate emerging technologies. You will be part of the team managing data governance, ensuring necessary data security and lifecycle controls are in place.
Your Qualifications and Skills
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical discipline
- 2+ years of hands-on experience in data engineering, ETL development, cloud-based data solutions , or building data products that serve analytics, automation, or machine learning needs
- Strong foundational knowledge of AWS cloud services, including S3, Lambda, Glue, and Snowflake, with a focus on scalable and cost-efficient data architectures
- Proficiency in Python, with experience in modularization, writing optimized, production-ready code for data transformations and automation
- Advanced SQL skills, including query optimization, performance tuning, and database design
- Experience in building robust and scalable data pipelines using AWS Glue, Step Functions and SQL-based transformations (using stored procedures)
- Solid understanding of data modeling, data warehousing concepts, and schema design best practices
- Hands-on experience with Tableau or other BI tools for data visualization and dashboard development
- Exposure to DevOps and CI/CD practices, including infrastructure-as-code, version control (Git), and automated deployment strategies
- Strong problem-solving mindset, with the ability to troubleshoot and optimize complex data workflows efficiently
- Excellent communication and collaboration skills, with the ability to work effectively in agile, cross-functional teams
- Experience with Databricks for scalable data processing and PySpark for distributed data transformations (preferred)
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