Data Engineering Manager - McKinsey Transformation

Key Skills

3D data processing, Alteryx, AWS Glue, Data Engineering, Data science techniques, Github, Machine learning techniques, PostgreSQL, Snowflake, SQL Server, Tableau, Terraform

Job Description

What You'll Do

You will manage a team of data engineers to architect, scale and maintain our transformation data platform, and to enable the development of new analytics offerings. You and your team will collaborate with software engineers, data scientists and analytics-focused consultants to integrate advanced analytics capabilities into the Wave product. 

You will also support the development of knowledge for the firm’s transformation consultancy group and help influencing many of the recommendations our clients need to positively change their businesses and enhance performance of their transformation program.

• Your key responsibilities will include:
• Acquiring, ingesting, and processing data from multiple sources and systems into centralized data marts
• Preparing data for analysis: profiling, cleaning, joining, transforming, enriching, aggregating, and filtering large and varied data sets
• Supporting data scientists: creating features, views, queries, datasets and data extracts through automation to help their analyses
• Adhering to Firm Information Security standards when requesting, extracting, ingesting and handling client data
• Creating reusable custom scripts, queries, and code commands for ad hoc data processing tasks

You will have the opportunity to gain new skills and build on the strengths you bring to the firm. In addition, you will be expected to coach and mentor other colleagues on data engineering topics, enabling them to grow and learn.

Qualifications

• Advanced degree in quantitative field like computer science, machine learning, applied statistics or mathematics; or equivalent experience
• Meaningful experience in building and maintaining large data sets to support data science development
• Ability to work across structured, semi-structured, and unstructured data, extracting information and identifying linkages across disparate data sets
• Ability to clearly communicate complex solutions to tech savvy and non tech savvy audiences
• Confirmed experience with the following technologies: AWS, Python, SQL, Tableau, GitHub
• Knowledge about infrastructure deployment tools like Terraform and GitHub Actions is a plus
• Meaningful experience with on-premise and cloud-based data management/warehousing: MS SQL Server, Oracle, PostgreSQL; Snowflake is a must
• 9+ years of relevant work experience
• Mastery of Information Security principles to ensure compliant handling and management of client data
• Ability to understand complex systems and solve challenging analytical problems
• Comfort with ambiguity and rapid changes common in early-stage product development
• Meaningful experience in Cloud platforms: Azure, Google Cloud; AWS is a must
• Meaningful experience in ETL tools: Alteryx, MS SSIS, Talend, Pentaho, Domo; AWS Glue is a must
• Meaningful experience in reporting and visualization tools: Power BI, MS SSRS; Tableau is a must