Description

Own the design, development, and maintenance of a secure, scalable data platform.

Responsibilities

• Engineer efficient, adaptable data pipelines to process high-volume data.
• Integrate diverse data sources including databases, APIs, SaaS platforms, files, logs, and events.
• Create standardized datasets to serve varied product and engineering use cases.
• Partner with Product and Engineering teams to ensure seamless integration of data solutions.
• Perform data quality checks on sources and automate quality control capabilities.

Required Skills

• 5+ years of experience as a Data Engineer.
• Hands-on experience with Star/Snowflake schema design, data modeling, and data pipelining.
• Expertise in Data Warehouse technologies such as Snowflake or AWS Redshift.
• Proficiency in AWS data pipelines: Lambda, AWS Glue, and Step Functions.
• Strong SQL skills and proficiency in Python or Java.
• Experience with MLOps practices.
• Proficiency with Git, GitHub, and JIRA.
• Experience with data analysis tools like Looker or Tableau.

Preferred Skills

• Experience in the Fintech or Financial Services industry.
• Familiarity with Pandas, Numpy, Scikit-learn, and Jupyter notebooks.
• Eagerness to learn about the Private Equity/Venture Capital ecosystem.

Key Skills

Education

Any Graduate