Data Engineer (Software Implementation)
McKinsey & Company
Data Engineer (Software Implementation)
Job ID: 102868
Your Impact
Your Growth
- 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.
Your qualifications and skills
- Design, build, and maintain end-to-end data pipelines leveraging Snowflake and Amazon S3 for ingestion, transformation, and storage
- Develop and enforce data quality frameworks (validation, anomaly detection, alerts) across ingestion and transformation layers.
- Set up and manage multiple Snowflake environments (Dev, Test, QA, Prod) with proper environment isolation, RBAC, and CI/CD practices.
- Lead and execute data migration initiatives from legacy/on-prem databases to Snowflake.
- Optimize Snowflake performance via clustering, materialized views, query profiling, and result caching.
- Develop and manage Snowflake Streams, Tasks, External Tables, File Formats, Stages, and Pipes for near real-time and batch processing.
- Implement Snowflake Snowpipe for continuous and automated data ingestion from S3.
- Manage and optimize virtual warehouses for performance and cost efficiency.
- Build reusable dbt models, implement modular transformations, and integrate into orchestration tools like Airflow or Dagster.
- Integrate Snowflake with BI tools and downstream applications securely using OAuth/JWT, Service Accounts, and External Functions.
- Apply data governance practices, including row-level security, column masking, and tag-based access control.
- 4+ years of experience in data engineering with at least 3+ years focused on Snowflake.
- Strong command of SQL (ANSI, Snowflake SQL dialect) and Python for scripting and transformation.
- Expertise in managing Snowflake features such as Warehouses, Databases, Schemas, Roles, Snowpipe, Streams & Tasks, External Tables, Data Sharing, Secure Views, Clustering Keys
- Experience with Snowflake Connector for Python, Snowflake REST API, and Snowflake's Native Apps or UDFs.
- Proficiency with CI/CD pipelines for Snowflake using tools like GitHub Actions
- Certified SnowPro Core and/or SnowPro Advanced: Data Engineer.
- Experience working with semi-structured data (JSON, Avro, Parquet) in Snowflake.
- Knowledge of data privacy & governance (e.g., PII handling, GDPR, HIPAA).
- Ability to communicate ideas most effectively in English - both verbally and in writing
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.
FOR BRAZILIAN APPLICANTS: Applicants for job positions in any office in Brazil have flexibility regarding qualifications and McKinsey & Company will not require previous experience of more than 6 months. If the job description indicates preferred prior work experience of more than 6 months, applicants for such job position in the Brazilian offices must interpret the preferred qualification described as limited up to 6 months maximum.
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Job Skill Code - SSDC - Software Delivery Specialist, Data
Function -
Industry -
Post to LinkedIn - Yes
Posted to LinkedIn Date - Fri Aug 29 00:00:00 GMT 2025
LinkedIn Posting City - Sao Paulo
LinkedIn Posting State/Province -
LinkedIn Posting Country - Brazil
LinkedIn Job Title - Data Engineer (Software Implementation)
LinkedIn Function - Engineering;Information Technology;Supply Chain
LinkedIn Industry - Computer Software;Information Technology and Services;Management Consulting
LinkedIn Seniority Level - Mid-Senior level