Data Engineer with Databricks

Role: Data Engineer with Data bricks  Location: Marlborough, NH Duration: 6 months Experience Required 5+ years of hands‑on data engineering experience 3+ years focused on the Databricks / Spark ecosystem Key Responsibilities Data Pipeline Development Design, develop, and deploy robust, scalable batch and streaming data pipelines using: PySpark Spark SQL Delta Live Tables Use Infrastructure as Code (IaC) tools such as: Terraform AWS DevOps GitHub Actions Champion CI/CD best practices for data pipelines. Work closely with: Functional Consultants Data Scientists Analytics Engineers Translate data requirements into well‑structured, consumption‑ready datasets. Required Skills & Qualifications Databricks & Spark Expertise Deep hands‑on experience with the Databricks Lakehouse Platform, including: Delta Lake Structured Streaming Delta Live Tables Cluster configuration and optimization Programming & Data Engineering Expert‑level proficiency in Python and PySpark. Advanced SQL skills for transformation, validation, and analysis. Strong understanding of ETL / ELT design patterns. Data Warehousing Concepts Strong knowledge of data modeling principles, including: Dimensional modeling (Kimball) Data warehousing fundamentals Strong familiarity with cloud storage (e.g., S3 or equivalent). Hands‑on experience with: Git version control Code reviews Testing CI/CD pipelines Preferred Qualifications (Nice to Have) Databricks Certified Data Engineer – Professional certification. Experience with Terraform or other IaC tools. Experience delivering data solutions in retail or e‑commerce environments. Familiarity with orchestration tools such as Airflow. Experience with modern data stack tools, including: Send me your resume to [Upgrade to PRO to see contact]