• Develop, construct, test, and maintain data architectures, including databases and large-scale processing systems. • Design, build, and optimize data pipelines and ETL/ELT processes leveraging Snowflake and Azure Services. • Develop and maintain Snowflake data warehouses, ensuring efficient data modeling, partitioning, and performance tuning. • Implement data flow processes that automate and streamline data collection, processing, and analysis. • Ensure data governance, quality, and security best practices across all data platforms. • Collaborate with analytics and business teams to improve data models that feed business intelligence tools, increasing data accessibility and fostering data-driven decisionmaking across the organization. • Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc. • Provide operational support for existing data infrastructure and develop new solutions as needed. • Monitor, troubleshoot, and optimize system performance in Azure and Snowflake environments. • Support CI/CD pipelines and automation for data workflows and deployments. • Keep current with industry trends and innovations in data engineering and propose changes to the existing landscape.

• You'll work on our data pipelines and build APIs that serve data to our product. • You'll own the full stack of our client-facing analytics and admin tool. • You'll implement data pipelines with DBT, Airflow, DynamoDB, and AWS Lambda. • You'll contribute front-end code to our core product to help integrate our data into product experiences. • You'll build out telemetry to power our analytics decision-making and machine learning models.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description As a Data Engineer, you will: - Build and maintain scalable, best-in-class data infrastructure and pipelines that serve as core components of a multi-tenant data platform. - Ensure our data pipelines and data warehouse are optimized for accuracy, performance, and accessibility. - Manage architecture frameworks and participate in the development of data, experimentation, and analytics solutions in collaboration with cross-functional partners in the Product and Engineering organizations. - Implement processes and systems to monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it. - Test and clearly document data assets and warehouse implementations to enable others to understand the implementation and definition of data methodologies easily. - Design data integrations and a data quality framework. - Work closely with Product and Engineering teams to develop a strategy for long-term data platform architecture. Qualifications - Demonstrated ability to build, manage, and optimize core data infrastructure at scale in a multi-tenant environment. - A propensity to independently identify opportunities for optimization and drive forward high-impact projects with minimal guidance. - Proficiency in SQL and strong programming skills in Python, with experience in Bash scripting for automation and workflow management. - Deep knowledge and experience with Snowflake and advanced features like Snowpipes, storage integrations, stages, streams, tasks. - Experience with the AWS ecosystem and securely deploying and managing applications using serverless tools like ECS and Lambda. - Experience building and maintaining custom ingestion pipelines using tools like dlt or requests. - Ingest data from third-party APIs and custom ingestion pipelines with Dagster and Snowflake (Snowpipe, streams, and tasks). - Proficiency with workflow orchestration tools (Dagster or similar tooling like Airflow or Prefect) and data transformation tools (dbt). - Experience with DataOps tools, such as Docker, GitHub Actions, and Terraform. - Experience with AI or ML is a plus. Requirements - Excited to build foundational data infrastructure that powers many e-commerce brands. - Energized by the opportunity to abstract repeated data problems into platform-level solutions. - Passionate about working cross-functionally across engineering, product, and data teams. - Motivated by working in a fast-paced and iterative environment. - Excited by the opportunity to be an early, critical member of a rapidly growing organization. - Personally aligned with our mission to make commerce accessible. Benefits - An investment in your physical and mental well-being; we offer 100% employee Medical Benefits coverage, with 69% dependent coverage. - Flexible PTO; we encourage you to take the time you need to be your best self at work. - An onboarding package and annual work from home stipend to ensure you have everything you need to be successful while working remote. - Generous Parental Leave with customizable transition back to work program. - The benefits of working from home, with opportunities to spend quality time with the team at Chord in-person events throughout the year. - To make an impact! We’re an early-stage company, which means there is space to champion ideas, and create and lead initiatives at any level in the Organization. - This is a full-time, salaried position that includes Equity.

• Implement monitoring systems and routines (data, applications, queries, etc.) • Evolve data models, architecture, and the construction of data pipelines • Implement data migration, processing, and storage routines (ETL) • Develop integrations between different data sources (RDS, external APIs, etc.) • Implement and execute load testing • Monitor running data pipelines