Databricks Engineer

Job Title: Databricks Engineer Job Type: Contract (W2) Start Date: ASAP Duration: 6 Months (with potential for extension) Work Location: Cincinnati, OH (onsite role) Work Schedule/Hours: Monday-Friday, 8 hours per day (standard business hours) Compensation: $58.00 to $65.00 per hour Overview: Our global consulting client is seeking an experienced Databricks Engineer to support enterprise data engineering initiatives focused on building scalable cloud-based data pipelines and lakehouse solutions. This role will play a key part in designing and supporting modern data architecture, enabling analytics, reporting, and business intelligence capabilities across the organization. The Databricks Engineer will partner with analysts, engineers, and business stakeholders to develop reliable data products and ensure high standards for data quality, integrity, governance, and performance. The ideal candidate will bring strong hands-on experience with Databricks, cloud data platforms, and modern data engineering best practices, with a focus on scalable ETL/ELT architecture and lakehouse frameworks such as Medallion architecture. Responsibilities: • Design, build, and maintain scalable data pipelines and lakehouse solutions using Databricks. • Develop and support ETL/ELT processes to transform and integrate enterprise data sources. • Partner with business stakeholders and analysts to translate data requirements into reliable datasets and data products. • Support cloud-based data architecture initiatives primarily within Azure environments. • Implement and optimize data models, database structures, and architectural patterns across relational and NoSQL systems. • Ensure data quality, integrity, governance, and security standards are maintained throughout the data lifecycle. • Develop and maintain workflow orchestration processes using tools such as Airflow or Luigi. • Support data organization strategies utilizing Medallion architecture (Bronze/Silver/Gold layers). • Contribute to centralized and decentralized data strategies, including Data Mesh principles. • Monitor, troubleshoot, and optimize performance of data systems and pipelines. • Collaborate cross-functionally with engineering, analytics, and business teams to support platform health and scalability. • Document technical processes, solutions, and architecture to support operational continuity. Required Qualifications: • High school diploma (or GED) required; college degree preferred. • 6+ years of experience in data engineering or related technical roles. • Hands-on experience with Databricks and core data engineering tools including SQL, Python, and Spark. • Experience designing and building scalable ETL/ELT pipelines and data workflows. • Experience with cloud data platforms, particularly Microsoft Azure. • Strong understanding of data modeling, data architecture, and database design across relational and NoSQL systems. • Knowledge of data governance, data quality, and security best practices. • Experience with workflow orchestration tools such as Airflow or Luigi. • Familiarity with Medallion architecture and Data Mesh concepts. • Strong problem-solving, communication, and technical documentation skills. Preferred Qualifications: • Experience with cloud data warehousing platforms such as Snowflake, Redshift, or BigQuery. • Exposure to BI and reporting tools such as Power BI or Tableau. • Experience with performance tuning, optimization, and troubleshooting of large-scale data systems. • Familiarity with machine learning platforms and data science workflows. • Experience with streaming or real-time technologies such as Kafka or Flink. • Professional experience with Go (Golang). • Experience working in regulated industries such as healthcare or financial services.