Data Engineer
General Atlantic is a global investment firm that partners with entrepreneurs and investors to build long-term value.
About General Atlantic
Founded in 1980, General Atlantic is a global investment platform focused on identifying and supporting companies with strong growth potential. Its strategies include growth equity, private credit, energy transition, and infrastructure investing. The firm provides patient capital, customized investment solutions, portfolio support, operational expertise, and value-creation services to entrepreneurs, portfolio companies, institutional investors, families, endowments, foundations, and other capital partners.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
Join the Data Strategy team as an Associate-level Data Engineer reporting to the VP, Head of Data Engineering. Support cloud-based data pipelines, integration frameworks, self-service data platforms, and enterprise-grade data solutions while collaborating with engineering, product, infrastructure, security, and application development teams.
Requirements
- Bachelor's degree in Computer Science, Information Systems, Engineering, or equivalent practical experience
- 2–4 years of experience in data engineering, analytics engineering, or a related technical role
- Exposure to financial services or enterprise data environments is a plus
- Proficiency in Python and SQL
- Hands-on experience with Databricks, Snowflake, or similar data platforms
- Familiarity with cloud data services, especially Azure, including data lakes, warehouses, and orchestration tools
- Experience with structured and semi-structured data from APIs, SaaS platforms, and databases
- Understanding of ETL / ELT, data modeling, and pipeline monitoring
- Exposure to Power BI or Tableau is a plus
- Strong problem-solving skills and attention to detail
- Ability to learn quickly and adapt in a fast-paced environment
- Comfort working collaboratively within cross-functional teams
- Clear written and verbal communication skills
Responsibilities
- Support the design, development, and maintenance of cloud-based data ingestion and integration pipelines
- Build and maintain ETL / ELT workflows using Python, SQL, Spark, and Databricks
- Assist in integrating data from SaaS platforms, APIs, databases, and cloud applications
- Contribute to reusable data integration components and frameworks
- Monitor data pipelines, troubleshoot issues, and support production operations
- Assist in developing centralized data services and APIs for analytics, reporting, and application teams
- Support logical data models and service-layer abstractions
- Participate in batch and near-real-time data processing workflows
- Contribute to modernization initiatives migrating legacy data processes to cloud-native solutions
- Prepare curated datasets for data lakes, enterprise data hubs, and data warehouses
- Support scalable data storage and compute solutions using Databricks and cloud data services
- Enable reliable data access for analytics, reporting, and data science use cases
- Develop and maintain SQL objects, data models, and transformations
- Write maintainable Python code for data processing and orchestration
- Participate in code reviews, testing, and documentation to ensure data quality and reliability
Benefits
- Medical insurance
- Retirement savings contributions
- Mental and physical health resources
- Equal pay program
- Annual discretionary bonuses
- Long-term incentive programs