Senior Data Engineer

Responsibilities

• Architect, design, and implement scalable, reliable data solutions and pipelines aligned with business analytics needs
• Manage and fine-tune cloud resources and workloads for maximum performance, reliability, and cost-efficiency
• Lead the development of ETL/ELT processes for both batch and real-time data processing
• Partner with Product, Engineering, and Data Science teams to deliver effective, data-driven solutions
• Promote and enforce best practices in data governance, security, and data quality frameworks
• Provide technical leadership and mentorship to the team, ensuring architecture quality and best practices
• Maintain comprehensive documentation of data architectures, configurations, and workflows

Requirements

• 5+ years of hands-on data engineering experience in a production environment
• Strong proficiency in Python, SQL (complex queries, performance tuning), and PySpark/Apache Spark
• Expert knowledge of data modeling (3NF, Star, Snowflake Schema) and Lakehouse/Warehouse architectures
• Proven experience building pipelines using tools like dbt, Airflow, Dagster, or native cloud orchestrators
• Deep expertise in at least one major cloud ecosystem (AWS, GCP, Azure, Snowflake, or Databricks)
• Proficiency in Git workflows, CI/CD pipelines, and Infrastructure as Code (Terraform/CloudFormation)
• Experience integrating data from diverse sources including APIs, RDBMS/NoSQL, and streaming platforms like Kafka

About the Company

Founded in 2013, Fusemachines is a global provider of enterprise AI products and services on a mission to democratize AI. Leveraging proprietary AI Studio and AI Engines, the company helps drive clients' AI Enterprise Transformation. With offices in North America, Asia, and Latin America, Fusemachines provides a suite of enterprise AI offerings and specialty services that allow organizations of any size to implement and scale AI.