Senior Data Engineer

At the forefront of reimagining how industries operate, we are a team of builders and thinkers reshaping e-commerce, ticketing, and logistics from first principles. Our work is grounded in curiosity, experimentation, and a drive for real business impact. We eliminate inefficiencies—not just in code, but in legacy models and outdated assumptions.

• Expert-level Python proficiency for data engineering, including API integrations, data transformations (Pandas, PySpark), and automation
• Proven experience designing and deploying large-scale data platforms on AWS, GCP, or Azure
• Strong foundation in building production-grade ETL/ELT pipelines using Apache Airflow, Kafka, Spark, or cloud-native tools
• Hands-on experience with vector databases (e.g., Pinecone, Weaviate, Chroma, Milvus) and implementing semantic search
• Demonstrated knowledge of Generative AI and LLMs, with practical experience in RAG architectures and prompt engineering
• Deep understanding of data governance, quality, and documentation, with a focus on lineage, metadata, and compliance
• Familiarity with cloud services including serverless computing, managed databases, and data warehouses such as BigQuery, Redshift, or Snowflake
• Experience working with complex real-world data environments, including legacy systems, SaaS integrations, APIs, and databases
• Fluency in English, both written and spoken

• Analyze and optimize business processes by collaborating with stakeholders to uncover inefficiencies and define data requirements for automation
• Design scalable, modular data architectures that integrate with Generative AI and Agentic AI systems to support real-time decision-making
• Engineer robust ETL/ELT pipelines using Python, cloud-native services, and orchestration tools, supporting both batch and streaming data needs
• Architect RAG and vector database solutions using semantic search to enable LLMs to retrieve curated, context-rich business data
• Build intelligent data products, from predictive models and decision engines to AI-driven insights platforms
• Implement data quality, validation, and governance frameworks to ensure data integrity, lineage, and compliance across systems
• Lead technical discovery sessions with clients to transform complex business challenges into AI and data-driven opportunities
• Mentor team members on best practices in data engineering, AI integration, and modern cloud architectures