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Senior Data Engineer - I McKinsey Transformatics

McKinsey & Company

Data Science

Brussels, Belgium

Posted on Apr 9, 2025

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Transformation & Turnaround

Senior Data Engineer – I McKinsey Transformatics

Job ID: 96879

Brussels

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Do you want to work on complex and pressing challenges—the kind that bring together curious, ambitious, and determined leaders who strive to become better every day? If this sounds like you, you’ve come to the right place.

Your Impact

You will also be part of an effort to build next-generation data platforms on the cloud to enable our business stakeholders to have rapid data access and incubate emerging technologies. Additionally, you will mentor junior engineers, and implement data governance practices to ensure security, compliance, and lifecycle management.

In this role, you will design and build data products. You will develop and maintain scalable, reusable data products that serve as foundational assets for analytics, reporting, and machine learning pipelines.

You will be architecting and optimizing data pipelines You will lead the design, develop, and enhance ETL/ELT workflows using AWS Lambda, AWS Glue, Snowflake, and Databricks You will ensure high-performance, scalable, and cost-efficient data processing solutions.

You will manage and scale data infrastructure. You will oversee cloud-based data environments, configure optimized storage solutions (S3, Snowflake, Delta Lake), and manage compute resources for efficient data processing.

You will perform tuning and optimization. You will implement advanced query tuning, indexing strategies, partitioning techniques, and caching to maximize efficiency in Snowflake and Databricks.

You will check cross-functional collaboration. You will partner with data scientists, engineers, and business teams to deliver well-structured, analytics-ready datasets that drive insights and machine learning initiatives.

You will govern data, compliance and security. You will establish and enforce best practices for access control, data lineage tracking, encryption, and compliance with industry standards (SOC 2, GDPR).

You will automate and observe: build resilient, automated data workflows leveraging tools such as Step Functions and Databricks Workflows. You will implement proactive monitoring, logging, and alerting to ensure system reliability and data quality.

You will drive innovation and best practices. You will be responsible to mentor junior engineers, stay ahead of emerging technologies, participate in hackathons, contribute to internal knowledge sharing at team and company levels, and champion continuous improvement in data engineering methodologies.

Your Growth

You will work in our McKinsey Client Capabilities Network in EMEA and will be part of our Wave Transformatics team.

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 4 data engineers, 5 data scientists and 1 project manager 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 be responsible for designing, building, and optimizing scalable data solutions that power analytics, reporting, and machine learning. Working alongside a team of data engineers across global hubs, you will lead the development of robust data ingestion pipelines, procuring data from APIs and integrating it into cloud-based storage layers while ensuring data quality through rigorous cleaning and standardization.

Your qualifications and skills

Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field
5+ years of hands-on experience in data engineering, ETL/ELT development, cloud-based data solutions, or building data products that serve analytics, automation, or machine learning needs
Deep expertise in AWS cloud services, including S3, Lambda, Glue, Snowflake, and designing scalable, cost-efficient data architectures
Proficiency in Python, including modularization, writing optimized, production-ready code for data transformations, automation, and workflow orchestration
Expert-level SQL skills, including query optimization, performance tuning, stored procedures, and database design best practices
Proven experience in designing and implementing scalable data pipelines using AWS Glue, Step Functions, and SQL-based transformations (using stored procedures)
Strong knowledge of data modeling, data warehousing concepts, schema design, and partitioning strategies
Hands-on experience with Tableau or other BI tools for data visualization and dashboard development
Hands-on experience with DevOps and CI/CD, including infrastructure-as-code, version control (Git) and automated deployment strategies
Strong problem-solving skills, with a focus on troubleshooting and optimizing complex data workflows for performance, reliability, and scalability
Excellent communication and collaboration skills, with the ability to work effectively in agile, cross-functional teams and mentor junior engineers
Experience with Databricks for scalable data processing, PySpark for distributed data transformations, and Delta Lake for data versioning (Preferred)

Please review the additional requirements regarding essential job functions of McKinsey colleagues.

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FOR U.S. APPLICANTS: McKinsey & Company is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by applicable law.

FOR NON-U.S. APPLICANTS: McKinsey & Company is an Equal Opportunity employer. For additional details regarding our global EEO policy and diversity initiatives, please visit our McKinsey Careers and Diversity & Inclusion sites.

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Job Skill Group - N/A
Job Skill Code - GCYA - Senior Data Engineer I
Function -
Industry -
Post to LinkedIn - Yes
Posted to LinkedIn Date - Fri Apr 04 00:00:00 GMT 2025
LinkedIn Posting City - Brussels
LinkedIn Posting State/Province -
LinkedIn Posting Country - Belgium
LinkedIn Job Title - Senior Data Engineer – I McKinsey Transformatics
LinkedIn Function - Engineering
LinkedIn Industry - Architecture & Planning;Information Technology and Services
LinkedIn Seniority Level - Associate