You will join the Data Strategy team as an Associate-level Data Engineer, reporting to the VP, Head of Data Engineering. You'll work closely with senior data engineers, product managers, infrastructure, security, and application development teams to support the design, development, and maintenance of cloud-based data pipelines, integration frameworks, and self-service data platforms. This is a great opportunity if you are technically strong, highly curious, and eager to grow your expertise in modern data engineering tools and best practices while contributing to enterprise-grade data solutions.
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 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 for 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
- 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
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 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
- 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
Benefits
- Medical insurance
- Retirement savings contributions
- Mental and physical health resources
- Equal pay program
- Annual discretionary bonuses
- Long-term incentive programs