About the position
Atomic is the venture studio that co-founds companies by pairing founders with the best ideas, teams, and resources, and funding those with the most potential. When entrepreneurs co-found with Atomic, they team up with an experienced group of operators who have started dozens of companies and created billions of dollars in enterprise value. Industry disruptors like Bungalow, Found, Hims and Hers, Homebound, OpenStore, and Replicant all started at Atomic along with dozens more. Atomic was founded in 2012 by serial entrepreneur Jack Abraham and has offices in NYC, Miami, and San Francisco with a distributed team across North America. Housing is a vibrant field, and Bungalow's team is dedicated to enhancing the living experiences of our communities. Our mission is to deliver top-notch homes that blend quality with affordability, ensuring that finding the perfect place is a hassle-free experience. As the Lead Analytics Engineer, you will be the technical and strategic driving force behind our domain-driven analytical datasets and data pipelines. Your mission is to design, build, and optimize data architectures that empower functional leaders across Marketing, Sales, Operations, Product, and Executive teams. In this role, you will combine deep technical expertise in AWS, Airflow, Python, SQL, and DBT with strong business acumen to manage stakeholder requests and drive data-driven decision-making. You will lead cross-functional teams, mentor junior engineers, and collaborate with key stakeholders to transform complex business requirements into scalable, high-quality data solutions.
Responsibilities
- Translate business requirements into intuitive, domain-specific data models and set standards for data architecture.
- Architect, build, and optimize scalable pipelines using AWS, Airflow, and dbt to ensure high-quality data delivery.
- Work closely with cross-functional stakeholders to align technical solutions with business needs.
- Utilize advanced SQL and Python skills to develop efficient reports and analytical insights that drive decision-making.
- Implement best practices, and emerging technologies to maintain scalable, cost-efficient data processes.
Requirements
- 7+ years in analytics engineering, data consultancy, data engineering, or a related field, with significant experience in leading technical projects and managing stakeholder requirements.
- Proven experience with AWS services relevant to data warehousing, ETL/ELT processes, and scalable data architectures.
- Strong hands-on experience with Apache Airflow for orchestrating and managing complex data pipelines.
- Advanced proficiency in Python and SQL for data manipulation, reporting, and analytics. Demonstrated expertise with DBT for transforming and modeling data.
- Deep understanding of data modeling concepts, including star schema, snowflake schema, and dimensional modeling.
- Familiarity with business intelligence tools (e.g., Tableau, Looker, Metabase) for visualization and data exploration.
- Experience with Git and CI/CD practices to streamline and secure data deployments.
- Proven leadership abilities with experience in managing teams and mentoring junior engineers.
- Ability to balance technical depth with strategic business insight, ensuring that data initiatives drive measurable business value.
- Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
- Strong analytical and problem-solving skills, with meticulous attention to detail.
Nice-to-haves
- Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a related field.
A Smarter and Faster Way to Build Your Resume