Data bricks Developer
Location: [Remote]
Job Summary
We are seeking a Mid-Level Data Engineer / BI Developer with strong experience in Databricks, Python, and Power BI to design, develop, and maintain data pipelines, data models, and business intelligence solutions. The ideal candidate will work closely with business stakeholders and technical teams to transform raw data into actionable insights.
Key Responsibilities
- Develop and maintain scalable data pipelines using Databricks.
- Build ETL/ELT processes using Python and SQL.
- Design, develop, and optimize Power BI dashboards and reports.
- Create and maintain data models, datasets, and semantic layers.
- Integrate data from multiple sources and ensure data quality and consistency.
- Collaborate with business users to gather reporting and analytics requirements.
- Monitor, troubleshoot, and optimize data workflows and reporting solutions.
- Implement best practices for data governance, security, and performance.
- Support ad hoc reporting and analytical requests.
Required Skills
- 3–6 years of experience in Data Engineering, BI Development, or related roles.
- Hands-on experience with Databricks and Apache Spark.
- Strong programming skills in Python.
- Proficiency in SQL and database concepts.
- Experience developing interactive dashboards and reports in Power BI.
- Knowledge of data warehousing concepts and dimensional modeling.
- Experience with ETL/ELT development and data integration.
- Understanding of cloud platforms such as Azure, AWS, or Google Cloud Platform.
Preferred Skills
- Experience with Azure Data Factory (ADF) or similar orchestration tools.
- Knowledge of Delta Lake and Databricks optimization techniques.
- Familiarity with CI/CD processes and version control tools such as Git.
- Experience with Power BI DAX and Power Query.
- Exposure to Agile/Scrum methodologies.
Education
- Bachelor''s degree in Computer Science, Information Technology, Engineering, or a related field.
Nice to Have
- Databricks, Azure, or Power BI certifications.
- Experience working in large-scale data analytics environments.
Keywords: Databricks, Python, PySpark, Power BI, SQL, ETL, Data Engineering, Data Warehousing, Azure, Spark, DAX, BI Reporting.
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