Lead Data Engineer

Join Happen Bank as a Lead Data Engineer, where you'll lead the Financial Data Operations team and own the critical data pipelines that support key business functions. You'll act as a bridge between engineering, product, and business stakeholders, driving operational excellence through automation and AI-driven improvements. This role offers a hybrid work model, generous paid time off, and a range of health and wellness benefits.

• Lead the Financial Data Operations team, owning the pipelines that support month-end close, investor servicing, revenue recognition, and other high-impact processes.
• Act as the bridge between engineering, product, and business stakeholders while building team capability and driving operational excellence through smart automation and AI-driven improvements.
• Drive adoption of modern data platform capabilities, including Databricks, dbt, Elementary, and Dagster, while maintaining existing production systems.
• Strong expertise in SQL, data modeling, data warehouse concepts, and building production data pipelines at scale
• You have hands-on experience using AI tools to accelerate your work and improve output quality — you're equally comfortable using them yourself and showing colleagues how, and you're thoughtful about limitations and where human judgment matters most
• 7+ years of experience in data engineering, with 2+ years leading teams or projects in a technical lead capacity; bachelor's degree in a related field; or equivalent work experience
• Experience with orchestration tools such as Airflow, Oozie, or Dagster and distributed processing frameworks like Spark or PySpark
• Working knowledge of AWS services (EMR, S3, Redshift) and modern data platforms such as Snowflake or Databricks
• Strong communication and organizational skills with experience collaborating across business, product, and engineering teams
• You take ownership of outcomes, proactively identifying risks and workflow improvements before they become blockers
• You balance technical depth with business context, understanding how data pipelines support financial processes and regulatory requirements
• Experience leading or mentoring offshore engineering teams and managing work across time zones
• Experience with dbt for data transformation and Elementary for data validation
• Hands-on use of AI tools such as Claude, ChatGPT, or GitHub Copilot to improve development workflows
• Background in financial services, accounting systems, or investor reporting processes
• Experience building self-service analytics tools using Streamlit or similar frameworks
• Familiarity with data quality frameworks, alerting systems, and SRE practices for data infrastructure