Senior Data Engineer (Databricks/AWS)

Fusemachines

2d • Remote

About The Position

This is a full-time, high-impact position for a Senior Data Engineer with expertise in Databricks, dbt, and Apache Airflow to support a critical CRM data architecture migration for a key client in the Life Sciences industry. In this role, you will join an urgent initiative to backfill key engineering capabilities and maintain momentum during an ongoing CRM system transition. The project involves migrating enterprise customer data from Veeva CRM to Salesforce Life Sciences Cloud, integrated with an underlying AWS S3 cloud environment and Databricks data warehouse. Your main focus will be building out, configuring, and redirecting data ingestion pipelines out of Life Sciences Cloud into the data warehouse, while implementing dbt models and Airflow orchestrations to ensure complete data accuracy. Candidates must be able to operate strictly on US East Coast business hours (location is flexible across North America, LATAM, or remote with full Eastern Time overlap).

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).

Nice To Haves

• Databricks Certified Data Engineer Associate/Professional
• Databricks Spark Developer
• Major cloud certifications in AWS

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.

Benefits

• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed