Senior Data Engineer

Job Overview:
We are seeking a Spark/SQL ETL Data Engineer with strong expertise in designing, developing, and optimizing scalable data integration and transformation solutions. The ideal candidate will have hands-on experience with Apache Spark, SQL, Databases, and modern data engineering practices to support enterprise data pipelines and analytics initiatives.

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Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT data pipelines using Apache Spark and SQL
• Build and optimize batch and near real-time data processing workflows across large-scale datasets
• Develop data ingestion, transformation, and data quality frameworks for enterprise data platforms
• Work with Delta Lake, data lakes, and cloud-based big data environments to ensure reliable data processing
• Perform data modeling, query tuning, and performance optimization for large datasets
• Integrate data from multiple source systems, databases, and external platforms
• Implement data validation, monitoring, and troubleshooting processes to ensure data integrity
• Collaborate with business analysts, architects, and cross-functional teams to deliver data-driven solutions
• Support data governance, security, and compliance requirements across the data ecosystem

Required Skills

• Strong proficiency in Apache Spark (PySpark) and SQL
• Extensive experience developing and optimizing ETL/ELT pipelines
• Strong understanding of distributed data processing concepts and Spark architecture
• Experience working with relational and non-relational databases
• Proficiency in data modeling, performance tuning, and query optimization
• Experience with workflow orchestration and scheduling tools (e.g., Airflow, Control-M, Azure Data Factory, or similar)
• Familiarity with cloud data platforms such as Azure, AWS, or Google Cloud
• Strong problem-solving, analytical, and troubleshooting skills