Senior Data Engineer -Data Modelling

Unybrands was established in 2020 by a group of partners united by a shared vision: to build the leading next-generation e-commerce platform for micro-brands. Headquartered in Miami, the company has a global presence with teams in Berlin, London, New York, and China.

Unybrands acquires e-commerce businesses that sell both on and off Amazon. Once acquired, these brands are integrated into Unybrands' platform, where operations are optimized, business performance is enhanced, and expansion into new product lines and markets is driven. Currently we have acquired 30 brands including Pet Care, Personal Care, Home Care, Supplements, Baby & Juvenile, Garden & Outdoor, Sports & Fitness, and Home, Lifestyle Culinary & Arts. Through expert management and robust infrastructure, Unybrands empowers e-commerce brands to scale and thrive.

We’re looking for a seasoned Senior Data Engineer to help design and scale our next-generation data infrastructure. You’ll build robust data models and pipelines that power analytics, reporting, and machine learning for our e-commerce and retail platforms. If you’re passionate about data engineering and thrive in a dynamic environment, we’d love to hear from you.

Key Responsibilities

• Data Modeling: Design scalable data models (e.g., Dimensional, Data Vault) optimized for performance and future growth in BigQuery.

• Pipeline Development: Build and maintain fault-tolerant ETL/ELT pipelines using Python, SQL, and orchestration tools like Airflow and DBT.

• Cloud Data Warehousing: Drive best practices in schema design, query tuning, and cost optimization on BigQuery or similar platforms.

• Cloud Platforms: Utilize GCP and/or AWS for data ingestion, transformation, and orchestration.

• Data Governance: Ensure data quality, consistency, and lineage through governance and documentation.

• Performance Optimization: Identify opportunities to improve system efficiency and reduce costs.

• Mentorship: Provide technical guidance and foster best practices across the engineering team.

• Documentation: Maintain clear documentation for models, pipelines, and processes.

Requirements

• 8+ years in data engineering or a related role.

• Strong expertise in data modeling, SQL, and cloud data warehouses (BigQuery, Snowflake).

• Proficiency in Python and experience with modern data stack tools (Airflow, DBT, Git).

• Hands-on experience with GCP or AWS and their data services.

• Background in e-commerce, CPG, or retail preferred.

• Excellent problem-solving and communication skills.

What Sets You Apart

• Adaptability: Eager to learn and evolve with new technologies.

• Ownership: Take pride in delivering reliable, high-quality solutions.

• Collaboration: Team-first mindset with a willingness to share and learn.

• Impact Focused: Always thinking about how data drives business value.

• Problem Solver: Skilled at breaking down complex issues and finding practical solutions.