Data Engineer

The Role

We are building a modern data stack to empower data-driven decision-making across our engineering, finance, marketing, sales, product, and operations teams.

As a Data Engineer at Swan, you will take a leading role in designing, building, and scaling our core data infrastructure. This is a high-impact position with significant ownership, giving you the autonomy to influence our technical architecture, define best practices, and create a robust data platform that directly accelerates Swan's growth.

Your responsibilities

• Architect and Build: Design, implement, and own scalable data pipelines to ingest and process data from various internal and third-party sources
• Own the Warehouse: Manage and optimize our Redshift Serverless data warehouse, ensuring high performance, reliability, and cost-efficiency
• Model for Impact: Develop and scale our dbt project to deliver clean, reliable, and well-documented data models that empower business intelligence and analytics
• Partner with Stakeholders: Collaborate with product, marketing, and finance teams to define and implement robust event tracking schemas and ensure data consistency across the organization
• Ensure Data Integrity: Establish best practices for data quality, observability, and monitoring. You'll build alerts and proactive solutions using tools like Datadog to maintain trust in our data
• Integrate Critical Tooling: Assist with managing our Customer Data Platform (RudderStack) and integrate key data sources, such as ad platforms and email marketing tools, into our central warehouse
• Champion Data Governance: Partner with our security team to implement and uphold data governance standards, ensuring data quality, security, and privacy compliance

Skills and experience that will help you succeed

• Proven experience as a Data Engineer or Senior Analytics Engineer, ideally in a fast-paced startup environment where you've built systems from scratch
• Deep expertise in a data warehousing (Redshift Serverless preferred) and a strong understanding of performance optimization
• Expert-level SQL and Python proficiency for data pipelines and scripting
• Hands-on experience building and maintaining data modeling and transformation workflows with dbt
• Experience with modern data stack tools, including event streaming/ETL platforms (e.g., RudderStack, Fivetran) and data orchestration (e.g., Airflow, Prefect, Dagster)
• Solid understanding of core AWS services (e.g., S3, Lambda, IAM, Glue) and concepts.
• Experience working with data from major ad platforms (e.g., Google Ads, Meta Ads) and marketing automation tools, preferred
• Familiarity with BI tools like AWS QuickSight, Tableau, or Looker, preferred
• Experience with data governance and security in a regulated industry like FinTech, preferred
• US timezones only
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• Compensation for this role will be based on location and experience, and may include base salary, equity, benefits