Data Engineer

General Atlantic is a leading global investor with more than four and a half decades of experience providing capital and strategic support for over 830 companies throughout its history. Established in 1980, General Atlantic continues to be a dedicated partner to visionary founders and investors seeking to build dynamic businesses and create long term value. Guided by the conviction that entrepreneurs can be incredible agents of transformational change, the firm combines a collaborative global approach, sector specific expertise, a long-term investment horizon, and a deep understanding of growth drivers to partner with and scale innovative businesses around the world.

General Atlantic manages approximately $123 billion in assets under management, inclusive of all strategies, as of December 31, 2025, with more than 900 professionals in 20 countries across five regions.

In October 2024, General Atlantic acquired Actis, which now operates as its Sustainable Infrastructure business alongside its existing strategies in Growth Equity, Credit, and Climate. Actis is a leading global investor in sustainable infrastructure, delivering competitive returns for institutional investors and measurable positive impact for the countries, cities and communities in which it operates.

Key Purpose of Role

General Atlantic is seeking an Associate-level Data Engineer to join the Data Strategy team. This role will report to the VP, Head of Data Engineering, and will work closely with senior data engineers, product managers, infrastructure, security, and application development teams. This role will support the design, development, and maintenance of cloud-based data pipelines, integration frameworks, and self-service data platforms. This role is ideal for a technically strong, highly curious engineer who is eager to grow their expertise in modern data engineering tools and best practices while contributing to enterprise-grade data solutions.

Key Responsibilities (this list is not exhaustive)

• 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 heterogeneous sources including SaaS platforms, APIs, databases, and cloud applications.
• Contribute to the development of reusable data integration components and frameworks.
• Monitor data pipelines, troubleshoot issues, and support production operations.
• Assist in the development of centralized data services and APIs that enable downstream consumption by analytics, reporting, and application teams.
• Support the creation and maintenance of logical data models and service-layer abstractions.
• Participate in building batch and near-real-time data processing workflows.
• Contribute to modernization initiatives migrating legacy data processes to cloud-native solutions.
• Help prepare curated datasets for use in data lakes, enterprise data hubs, and data warehouses.
• Work with senior engineers to support scalable, performant 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 clean, maintainable Python code for data processing and orchestration.
• Participate in code reviews, testing, and documentation to ensure data quality and reliability.

Knowledge

• 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.

Technical Skills

• Proficiency in Python and SQL.
• Hands-on experience with modern data platforms such as Databricks, Snowflake, or similar.
• Familiarity with cloud data services (Azure preferred) including data lakes, data warehouses, and orchestration tools.
• Experience working with structured and semi-structured data from APIs, SaaS platforms, and databases.
• Understanding of ETL / ELT concepts, data modeling, and pipeline monitoring.
• Exposure to BI tools such as Power BI or Tableau is a plus.

Professional Skills

• Strong problem-solving skills and attention to detail.
• Ability to learn new technologies quickly and adapt in a fast-paced environment.
• Comfortable working collaboratively within cross-functional teams.
• Clear written and verbal communication skills, with the ability to explain technical concepts to non-technical stakeholders.

General Atlantic offers a robust reward program to all employees that will support you and your family, maintaining fulfilling, secure and healthy lives now and into the future, which includes but is not limited to medical insurance, retirement savings contributions, mental and physical health resources and an equal pay program. Additional reward programs, such as annual discretionary bonuses and long-term incentive programs, are available for eligible employees and are offered as recognition for performance and one's contributions towards the organization's success.

General Atlantic is an equal opportunity employer and does not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law.