Data Engineer

Overview

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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.

Key Responsibilities

• 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

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