Data Engineer
2 days ago
Job Post: Data Engineer
Experience: 8 - 11 Years
Location: Pittsburgh
Duration : 12 Months
Notice Period: 0 - 30 Days
Job Purpose
Design, construct, and maintain scalable data management systems using Azure Databricks, ensuring they meet end-user expectations. Supervise the upkeep of existing data infrastructure workflows and create data processing pipelines utilizing Databricks Notebooks, Spark SQL, Python, and other tools.
Key Responsibilities
- Interpret business requirements and collaborate with internal resources and application vendors.
- Design, develop, and maintain Databricks solutions and data quality rules.
- Troubleshoot and resolve data-related issues.
- Configure and create data models and quality rules to meet customer needs.
- Work with multiple database platforms, including MSSQL and Oracle.
- Optimize PySpark/Python code and SQL queries to improve performance.
- Design and implement ETL pipelines and effective data models.
- Document data pipeline architecture and processes.
- Communicate effectively with business and technology stakeholders.
- Deliver results under tight deadlines while adhering to quality standards.
Key Competencies
- Experience: 8+ years in data engineering with expertise in Azure Databricks, MSSQL, LakeFlow, and Python.
- Proficient in creating and optimizing data pipelines using Databricks Notebooks, Spark SQL, and PySpark.
- Knowledge of Azure services like Azure Data Lake Storage and Azure SQL Data Warehouse.
- Expertise in data warehousing, ETL pipeline development, and data governance.
- Hands-on experience with data quality rules using Databricks and platforms like IDQ.
- Strong problem-solving, analytical, and organizational skills.
- Ability to work independently and collaboratively in cross-functional teams.
Skills & Requirements
- Technical Skills: Azure Databricks, PySpark, SQL (MSSQL, Spark SQL), Azure Data Lake Storage, ETL, Data Modeling and Governance, Data Warehousing, Python.
- Soft Skills: Strong communication, problem-solving, and attention to detail.
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