We are seeking a highly motivated and technically proficient Data Engineer to join our growing data and analytics team. This role involves designing, developing, and optimizing scalable data pipelines and integrations across various cloud-based and third-party platforms. The ideal candidate will have hands-on experience with Databricks, Apache Spark, PySpark, and cloud computing, along with strong problem-solving skills and a solid understanding of data architecture and integration best practices.

REQUIRED SKILLS AND QUALIFICATIONS:

• 5+ years of experience in data engineering, software development, or a related role.
• Strong hands-on experience with:
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• Databricks, Apache Spark, PySpark

• SQL and cloud-native or relational databases
• Python programming for data integration and processing
• API development and integration experience with Postman, Swagger, REST APIs
• Proficiency in working with AWS Cloud or similar platforms (S3, Lambda, AppFlow, etc.)
• Strong understanding of data pipelines, ETL/ELT, and data architecture principles
• Experience integrating data from platforms like Salesforce, HubSpot, or similar CRMs
• Strong problem-solving skills and ability to work in fast-paced environments
• Excellent communication and collaboration skills

PREFERRED QUALIFICATIONS:

• Bachelor’s degree in computer science, Data Engineering, or a related technical field
• Experience with Delta Lake, Databricks DLT (Delta Live Tables), and Unity Catalog
• Familiarity with data governance, data cataloging, and access control mechanisms
• Experience with GitHub, Jira, and Confluence for code management and team collaboration
• Expertise in Scrum methodology and Agile team environments
• Familiarity with data orchestration and transformation tools such as dbt or Airflow
• Experience with event-driven architectures and real-time data (e.g., Kafka)
• Certifications in Databricks, AWS, or other cloud platforms (a plus)
  All qualified applicants will receive consideration for employment without regard to race, color, national origin, age, ancestry, religion, sex, sexual orientation, gender identity, gender expression, marital status, disability, medical condition, genetic information, pregnancy, or military or veteran status. We consider all qualified applicants, including those with criminal histories, in a manner consistent with state and local laws, including the California Fair Chance Act, City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, and Los Angeles County Fair Chance Ordinance. For unincorporated Los Angeles county, to the extent our customers require a background check for certain positions, the Company faces a significant risk to its business operations and business reputation unless a review of criminal history is conducted for those specific job positions

• Develop and optimize data pipelines and workflows using Databricks, Apache Spark, PySpark, and cloud-native services.
• Integrate data from internal systems and external platforms such as HubSpot, Salesforce, and other CRM systems via APIs.
• Implement cloud-based data architectures following data mesh principles and best practices.
• Collaborate on data modeling, transformation, and quality assurance for analytics and reporting purposes.
• Build and maintain APIs; use Postman and Swagger for testing and documentation.
• Write efficient and modular code in Python and leverage SQL for data processing.
• Follow SDLC best practices including version control, CI/CD, and code reviews.
• Ensure data security, integrity, and governance across the full data lifecycle.
• Use AWS (or similar platforms like Azure or GCP) for compute, storage, and orchestration services.
• Work closely with cross-functional teams using Agile/Scrum methodologies.