Role Overview
A Senior Data Engineer is needed to build and maintain robust, scalable data infrastructure primarily within Databricks. This position plays a central role in enabling data-driven decision-making across two internal departments by delivering efficient, production-grade pipelines in a cloud-first environment. The role operates fully remotely and requires a self-directed approach with strong communication and technical execution.
Key Responsibilities
- Design, implement, and refine data workflows in Databricks, prioritizing performance and scalability
- Develop automated ETL and ELT processes that follow enterprise standards for reliability and security
- Support cloud-based data modeling, pipeline orchestration, and data quality assurance
- Collaborate with stakeholders to understand requirements and improve data delivery
- Utilize Microsoft Fabric for integration, analytics, and reporting tasks as needed
- Integrate and maintain pipelines involving Oracle databases and associated services
- Provide limited support for legacy systems including SQL Server, SSIS, SSRS, and SSAS
- Ensure datasets are accurate, accessible, and well-documented across platforms
Required Qualifications
- Proven experience with Databricks, including Spark, Delta Lake, and notebook development
- Strong command of Python, PySpark, and SQL for distributed data processing
- Background in cloud data engineering within large-scale organizational settings
- Familiarity with Microsoft Fabric, Power BI, or related analytics tools
- Working knowledge of traditional Microsoft data platforms (SQL Server, SSIS, SSRS, SSAS)
- Experience connecting and processing data from Oracle database systems
- Ability to design secure, maintainable ETL/ELT pipelines using industry best practices
- Excellent documentation habits and clear communication with technical and non-technical partners
Preferred Background
- Experience modernizing or migrating legacy data and BI platforms
- Knowledge of data quality frameworks, testing methodologies, or monitoring systems
- Exposure to Azure Data Factory, Synapse Analytics, or similar Microsoft cloud services
Technical Environment
Core technologies include Databricks, Spark, Delta Lake, Python, PySpark, SQL, Microsoft Fabric, Power BI, SQL Server, SSIS, SSRS, SSAS, Oracle databases, Azure Data Factory, and Synapse.
Work & Compensation
- Fully remote role with global flexibility
- Weekly commitment of 35 to 40 hours
- Hourly rate between $23.75 and $25.00 USD
Team Culture
This role thrives in an environment of independent ownership and proactive problem solving. You should be comfortable managing your workload with minimal oversight while adapting to evolving priorities. Collaboration with cross-functional partners is essential, and a commitment to accountability and clear communication is expected.
