Data Architect

Key Skills

Python Programming, PySpark, SQL, Apache Airflow, Databricks, Kedro, AWS, Google Cloud Platform (GCP), Azure, Scala Programming, RDBMS, PostgreSQL, Amazon RedShift, Teradata, Snowflake, NoSQL, Apache Cassandra, Neo4J, Titan, MongoDB

Job Description

Who You'll Work With

You will work in our New Jersey, New York, San Francisco or Silicon Valley office as part of McKinsey Digital.

Despite being part of a large, multinational organization, our group works more like a small startup company, where differences are appreciated. Our development teams are small, flexible, and employ agile methodologies to quickly provide our consultants with the solutions they need. We combine the latest open source technologies with traditional enterprise software products. Our office culture is casual, fun, and social, with an emphasis on education and innovation. With McKinsey, you'll have the freedom to try new ideas and be creative, constantly learning and growing. We also emphasize mentoring, coaching, and support to help you build on your current skills.

McKinsey Digital uses the latest technology disruptions (e.g., cloud, big data, mobile, agile, software development) and a team of talented technologists to rapidly build and deploy custom web and mobile Business intelligence applications for our clients. McKinsey Digital works closely with our consultants and clients to develop a deep understanding of business needs and create tools that enable our clients to be more productive (e.g., equip frontline with mobile sales app) and make timely decisions (e.g., management dashboards). McKinsey Digital end-products range from building iPad demos and dashboards to technology environments or SaaS solutions, and to build targeted web/mobile applications.

What You'll Do

You will work hand-in-hand with colleagues and our clients to provide expertise in building digital data systems and platforms.

In this role, you’ll have the opportunity to lead a team in finding innovations in data by using established tools and techniques or by innovating new ones. You will provide strategic direction, design and drive architecture and implementation planning for our clients and act as a big data evangelist, educating McKinsey's and client's teams on big data architecture topics.

You will work with our clients to model their data landscape and define secure data exchange approaches. Alongside the team and the client, you will define the technology stack to be provisioned by the infrastructure team.

This is a hybrid client-facing/technical role using state of the art technologies, whilst also being able to communicate complex intractable ideas to non-technical audiences. Collecting clear requirements is a key part of this role and will define the technical strategy the team employs in the study.

Qualifications

• Bachelor's degree in computer science or other technically focused degree; master's degree preferred
• Years of combined hands-on software and client-facing experience within larger-scale big data projects such as migration and IT transformation (e.g. data lakes migration, re-platforming to different platform warehouses, working across stakeholder groups, etc.)
• Experience building highly scalable and secured solutions, data modeling, design patterns
• Experience building architecture to transform legacy to modern data platforms
• Experience in multiple database technologies such as distributed processing (Spark, Hadoop, EMR), MPP (AWS Redshift, Presto, Athena, Teradata), NoSQL (MongoDB, DynamoDB, Cassandra), graph (Neo4J, Titan)
• Proficiency in visualization toolsw (Tableau, D3, etc.)
• Expertise in data governance, data lineage, data quality and master data management
• Knowledge of agile software development process and familiarity with performance metric tools
• Distinct customer focus and quality mindset
• Strong analytical and problem-solving skills; ability to develop creative and efficient solutions
• including tolerance in dealing with bad quality data
• Ability to work at an abstract level and build consensus; ability to see from and sell to multiple viewpoints
• Ability to work efficiently with a solid sense for setting priorities; ability to guide your own learning and contribute to domain knowledge building
• Excellent interpersonal, leadership, and communication skills and the ability to work both independently and with a team