Lead Data Engineer
Fusemachines is a leading AI strategy, talent, and education services provider. Founded by Sameer Maskey Ph.D., Adjunct Associate Professor at Columbia University, Fusemachines has a core mission of democratizing AI. With a presence in 4 countries (Nepal, the United States, Canada, and the Dominican Republic and more than 250 full-time employees) Fusemachines seeks to bring its global expertise in AI to transform companies around the world.
About the role
This is a full time position
- Design and develop high-performance data architectures, which support data warehousing, real-time ETL, and batch big-data processing
- Design, develop, conducts unit testing, and maintain complex Tableau reports for scalability, manageability, extensibility, performance, and re-use.
- Resolve support tickets related to Tableau reports
- Collaborate with Product, Engineering, Science, Data analysts, and data scientists to implement rich and re-usable datasets/metrics
- Care about architecture, observability, testing, and building reliable infrastructure and pipelines
- Conduct Discovery of existing Data Infrastructure and Proposed Architecture
- Evaluate, design, and implement the data pipelines, data lineage, and data governance frameworks that are suitable for a modern analytics solution, considering industry-standard best practices and patterns.
- Data migration (if needed)
- Assess best practices and design a schema that matches business needs for delivering a modern analytics solution (descriptive, diagnostic, predictive, prescriptive)
- Possesses strong leadership skills with a willingness to lead, create Ideas, and be assertive
Requirements for the role
- 5+ years of real-world development experience with big-data platform
- Bachelor’s degree in computer science, data science, IT, or related field of study or equivalent experience
- Experience in tools like Talend and/or similar ETL tools
- Proven experience in developing and working Tableau driven dashboards, analytics
- Advanced Tableau development skills required
- Evaluated and implemented data solutions in AWS, Azure, or Google Cloud
- Experience with big data tools
- Experience with relational SQL and NoSQL databases, including Postgres, MongoDB, ElasticSearch
- Expert knowledge of SQL, Python, and database patterns and practices
- Experience with Spark/PySpark and other streaming data pipelines
- Knowledge of and aptitude for machine learning development and implementation
- Strong analytical skills
- High degree of organization, individual initiative, and personal accountability
- Astute with high resilience and the ability to achieve results and milestones in uncertain development situations.
Equal Opportunity Employer: Race, Color, Religion, Sex, Sexual Orientation, Gender Identity, National Origin, Age, Genetic Information, Disability, Protected Veteran Status, or any other legally protected group status.