Senior Data Engineer (Databricks/AWS)

Fusemachines is an AI company dedicated to delivering advanced AI products and solutions across various industries. They are seeking a Senior Data Engineer to support a critical CRM data architecture migration for a key client in the Life Sciences industry, focusing on building and optimizing data pipelines and ensuring data accuracy during the transition.

Responsibilities:

• Architect, build, and deploy data integration pipelines connecting Salesforce Life Sciences Cloud to the client’s Databricks warehouse environment
• Execute pipeline modifications to transition legacy data feeds from Veeva CRM to Salesforce Life Sciences Cloud, updating warehouse models accordingly
• Write clean, modular dbt transformation models and organize end-to-end DAG execution using Apache Airflow
• Manage Delta tables and optimize Databricks clusters and AWS S3 storage for high performance and cost efficiency
• Implement data quality testing, schemas, and verification rules in dbt and Python to guarantee accurate data delivery
• Build and enforce proactive monitoring frameworks
• Work closely with project leads, solution architects, and technical stakeholders during US East Coast hours to ensure rapid iteration and goal completion

Requirements:

• 5+ years of hands-on data engineering experience with deep expertise in AWS, Databricks, dbt, and Apache Airflow
• Strong programming proficiency in Python / PySpark and Advanced SQL (complex joins, analytical window functions)
• Hands-on expertise in Databricks platform architecture, Lakehouse implementation, Delta Lake, Unity Catalog, and cluster performance tuning
• Proven track record of architecting and executing migrations
• Demonstrated experience scaling platform performance
• Proven experience building scalable transformations pipelines using dbt for data transformation, testing, and documentation
• Solid background orchestrating complex workflow DAGs with Apache Airflow
• Experience working with AWS cloud infrastructure, specifically AWS S3 as an underlying data lake storage layer
• Hands-on experience developing integrations and data ingestion pipelines for CRM platforms, specifically Salesforce, Salesforce Life Sciences Cloud, and/or Veeva CRM
• Understanding of data structures, customer master data, and analytics workflows within the Life Sciences
• Deep understanding of SDLC/Agile and DevOps for CI/CD and artifact management
• Knowledge of AWS and Databricks security best practices and compliance standards
• Ability to maintain 100% full working time overlap with US East Coast business hours (ET)
• Databricks Certified Data Engineer Associate/Professional
• Databricks Spark Developer
• major cloud certifications in AWS