The candidate will be responsible for building and maintaining scalable, high-performance data infrastructure using SQL Server and modern data engineering tools.Requirements: Minimum 6 years of experience as a Data Engineer or in a similar role Strong expertise in SQL Server, T-SQL, and database design principles Proficiency in Python for writing clean, maintainable code Hands-on experience with Apache Spark for large-scale data processing Knowledge of Apache Hive for data warehousing solutions Experience with Apache Airflow for orchestrating complex data workflows Familiarity with Databricks and Azure Data Factory (minimum 1 year) Excellent problem-solving and analytical skills Strong understanding of data integrity, security, and performance optimization Responsibilities: Design and implement scalable data pipelines using Apache Spark and Python Develop and maintain data warehousing solutions with Apache Hive Orchestrate and monitor data workflows using Apache Airflow Manage, query, and optimize SQL Server databases Collaborate with data scientists, analysts, and stakeholders to define and deliver data solutions Ensure data quality, integrity, and security across all systems Troubleshoot and optimize data processing jobs and production systems Monitor database performance and tune systems for reliability and efficiency