Do you want to do work that matters, alongside supportive leaders who will help you grow faster than you ever thought possible? Are you a creative problem-solver who is energized by challenges? You’ve come to the right place.
YOUR IMPACT
Wave is a McKinsey SaaS product that equips clients to successfully manage improvement programs and transformations. Focused on business impact, Wave allows clients to track the impact of individual initiatives and understand how they affect longer term goals. It is a mix of an intuitive interface and McKinsey business expertise that gives clients a simple and insightful picture of what can otherwise be a complex process by allowing them to track the progress and performance of initiatives against business goals, budget and time frames.
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 GROWTH
Driving lasting impact and building long-term capabilities with our clients is not easy work. You are the kind of person who thrives in a high performance/high reward culture - doing hard things, picking yourself up when you stumble, and having the resilience to try another way forward.
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:
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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