Data Engineer

We are seeking an exceptional Data Engineer to help scale the data foundations that power a high-growth, data-driven organization. This individual will design, build, and optimize data pipelines and infrastructure that enable data to be a strategic asset across the business.

This role is highly collaborative, partnering with Product, Engineering, Analytics, and business stakeholders to quickly understand evolving challenges and deliver scalable, maintainable, high-quality solutions.

Data sits at the core of the organization’s operations. The business relies on clean, reliable, well-structured data to drive decision-making, enhance client experiences, and support a rapidly expanding product suite. This individual will be responsible for moving and transforming data, developing a deep understanding of business context, and enabling teams to act on insights.

Responsibilities

• Develop and automate large-scale, high-performance data pipelines and infrastructure to support business growth and data-driven decision-making
• Design and build reusable components and frameworks for data ingestion, cleansing, and quality assurance
• Streamline ingestion of raw data from multiple sources into data lake and warehouse environments
• Design scalable data models optimized for storage and retrieval across key business domains
• Partner closely with cross-functional teams including Operations, Sales, and Product to support strategic initiatives and improve business outcomes

• 6-10 years of experience in data engineering or data-focused software engineering roles
• Strong proficiency in Python and SQL
• Experience with orchestration frameworks such as Airflow, Prefect, or Dagster
• Deep understanding of OLAP (e.g., Snowflake, Databricks) and OLTP (e.g., PostgreSQL, MongoDB) systems, as well as ELT frameworks like dbt
• Experience building and deploying in cloud environments (AWS, GCP, or Azure)
• Strong software engineering fundamentals, including object-oriented and/or functional programming
• Experience with stream processing frameworks (e.g., Kafka, Spark, Flink)
• Familiarity with infrastructure-as-code tools (e.g., Terraform or CloudFormation)
• Detail-oriented with the ability to manage multiple priorities in a fast-paced environment
• Strong communication skills and ability to work both independently and collaboratively
• Interest in learning and applying modern data technologies

Preferred

• Experience with JVM-based languages such as Scala, Java, or Kotlin
• Exposure to financial services, markets, or investment-related data

The company offers a competitive compensation package including base salary, equity, and performance-based bonus. Benefits include comprehensive healthcare coverage, retirement plan with employer match, paid parental leave, and flexible paid time off. This role follows a hybrid schedule, with in-office collaboration during the week and flexibility for remote work.