About YouYou are responsible for helping to build and maintain the infrastructure that powers critical business reporting, advanced analytics, and data-driven decision-making across the company. This role requires someone who thrives in complex data environments, solves ambiguous problems with clarity, communicates effectively with both technical and non-technical stakeholders, is curious, resourceful, and eager to learn new tools and systems.
Job Duties & Responsibilities- Design, build, and maintain reliable data pipelines using Databricks, Delta Live Tables, and Azure Data Factory.
- Structure and manage Power BI semantic models using Tabular Editor and deployment pipelines.
- Diagnose and resolve data issues spanning multiple systems, including ADF, Databricks, and Power BI.
- Apply strong debugging skills to identify root causes of data mismatches, pipeline failures, and performance issues.
- Collaborate with stakeholders across business functions to clarify data needs and communicate technical concepts.
- Contribute to continuous improvement of our data infrastructure, identifying and implementing scalable solutions.
Specifications- Bachelor's degree in Computer Science, Information Systems, Statistics, Engineering, or related field preferred.
- 5+ years of experience in a data engineering, BI engineering, or similar technical role.
- Hands-on experience building pipelines with Databricks and/or Azure Data Factory.
- Strong proficiency with Python for data manipulation and transformation.
- Working knowledge of Power BI, including dataset design, relationships, and refresh behavior.
- Experience working in Git-based workflows.
- Demonstrated skill in debugging issues spanning ingestion, transformation, and reporting layers.
- Clear written and verbal communication skills, especially when explaining technical topics to non-technical stakeholders.
- Strong collaboration skills - shares knowledge, coordinates effectively, and communicates blockers early.
- Proven ability to prioritize and problem-solve in ambiguous or high-pressure situations.
- Proactive approach to improving reliability, performance, or maintainability of existing systems.
- Experience in AI, machine learning, or emerging data technologies - especially where they intersect with analytics and reporting.
- Designing and developing AI solutions using common industry cloud platforms such as Microsoft Azure, Databricks, AWS, or Fabric
- Knowledge of Power BI Premium capacity and refresh management.
- Exposure to metadata-driven frameworks and config-based pipeline logic.
- Familiarity with Unity Catalog, Terraform, or other emerging Databricks tools.
- Experience in automation, optimization, and reducing manual overhead in analytics systems.
