Description

You will architect and design large-scale data platforms, data warehouses, and streaming applications.

Responsibilities

• Design and implement data ingestion, integration, and distribution pipelines.
• Lead cloud data modernization, migration, and event-driven architecture initiatives.
• Transition traditional data architectures to next-gen platforms like distributed data lakes and data mesh.
• Manage competing deadlines and prioritize efforts across multiple projects with stakeholders.
• Operate independently within ambiguous environments to deliver management-ready materials.

Required Skills

• 12+ years of practical experience in Data Architecture and Engineering.
• Expertise in MPP technologies including Snowflake, BigQuery, or AWS Redshift.
• Hands-on experience with Databricks Unity Catalog and medallion architecture.
• Proficiency in Python, PySpark, and Java.
• Experience with Cloud Data Platforms including AWS, Azure, or Google Cloud Platform.
• Deep knowledge of traditional RDBMS such as Teradata, Netezza, MS SQL Server, Oracle, MySQL, or PostgreSQL.
• Practical application of data warehousing, data hub, MDM, and ODS practices.
• Experience with data integration tools like Informatica or Talend.
• Degree in a quantitative field such as Engineering, Computer Science, Statistics, or Finance.

Preferred Skills

• Experience within financial services or capital markets.
• Prior consulting experience.

Key Skills

Education

Any Graduate