We are seeking an exceptional Senior Data Platform Engineer to architect and develop a highly scalable data infrastructure for a fast-growing AI-powered vertical software startup revolutionizing retail and commerce operations. This role requires designing robust data systems capable of handling massive financial and operational datasets while delivering real-time insights through advanced AI integration. You will work with cutting-edge data technologies to build the backbone that powers financial forecasting, demand planning, and inventory optimization for leading eCommerce brands at enterprise scale.
Key Responsibilities:
Design and implement highly scalable data warehouse architecture and ELT/ETL pipeline systems.
Build robust data processing pipelines capable of handling massive datasets from diverse eCommerce sources.
Develop real-time data quality monitoring and fault tolerance systems across the entire data stack.
Design secure, performant data integrations from external sources to enrich the Drivepoint platform.
Optimize database queries and pipeline performance for speed and cost efficiency at scale.
Implement new customer-facing features using TypeScript and Python across multiple product areas.
Integrate AI/LLM-powered analytics capabilities into data processing workflows.
Collaborate with cross-functional teams, including product managers, customer success, and business stakeholders.
Ensure data integrity, security, and compliance across all financial and operational data processing.
Required Skills and Qualifications:
6+ years of experience in data engineering with strong expertise in SQL-based data warehouses (BigQuery or Snowflake).
Extensive experience building and optimizing ELT/ETL pipelines using Airbyte/Fivetran, DBT, and Airflow.
4+ years of professional software engineering experience with TypeScript and/or Python.
Proven track record in designing and building high-scale distributed data systems.
Strong database design and optimization skills for performance-critical financial analytics applications.
Experience with modern SDLC frameworks and the ability to deliver both infrastructure and customer-facing features.
Demonstrated ability to architect systems for massive scale, reliability, and fault tolerance.
Strong analytical and problem-solving capabilities with complex data processing challenges.
Excellent communication skills and collaborative approach to technical and business challenges.
Ability to thrive in a fast-paced startup environment with rapidly evolving requirements.
Preferred Skills and Qualifications:
Direct experience with financial data processing, forecasting, or eCommerce analytics platforms
Experience integrating AI/ML models and building AI agent-powered data processing features
Familiarity with real-time data streaming and event-driven architectures
Experience working with retail, eCommerce, or financial technology data at scale
Knowledge of data governance, quality frameworks, and observability best practices
Experience with cost optimization strategies for large-scale data processing workloads
Understanding of financial modeling, forecasting methodologies, and business intelligence requirements
Comfortable using modern AI tools to accelerate development and problem-solving workflows
