Sr. Data Engineer

As a skilled Data Engineer, your role will involve designing, building, and maintaining robust data pipelines and infrastructure to optimize data flow, ensure scalability, and enable seamless access to structured/unstructured data across the organization. Your expertise in designing, building, and optimizing scalable data pipelines with strong SQL proficiency and data modeling skills will be essential for this role. Responsibilities: - Design, develop, and maintain scalable pipelines to process structured and unstructured data. - Optimize and manage SQL queries for performance and efficiency in large-scale datasets. - Collaborate with data scientists, analysts, and business stakeholders to translate requirements into technical solutions. - Experience in implementing solutions for streaming data (e.g., Apache Kafka, AWS Kinesis) is preferred but not mandatory. - Ensure data quality, governance, and security across pipelines and storage systems. - Document architectures, processes, and workflows for clarity and reproducibility. Requirements: - 4 or more years of experience in Data Engineering. - Expertise in SQL (complex queries, optimization, and database design). - Solid understanding and hands-on experience in creating data pipelines and patterns. - Proficiency in programming languages like Python or R for scripting, automation, and pipeline development. - Hands-on experience with Google BigQuery and Apache Airflow. - Experience working on cloud-based platforms like AWS, GCP, or Azure. - Familiarity with structured data (RDBMS) and unstructured data (JSON, Parquet, Avro). - Knowledge of cloud-based data warehouses (Redshift, BigQuery, Snowflake). - Familiarity with version control systems (e.g., Git) and CI/CD practices. As a skilled Data Engineer, your role will involve designing, building, and maintaining robust data pipelines and infrastructure to optimize data flow, ensure scalability, and enable seamless access to structured/unstructured data across the organization. Your expertise in designing, building, and optimizing scalable data pipelines with strong SQL proficiency and data modeling skills will be essential for this role. Responsibilities: - Design, develop, and maintain scalable pipelines to process structured and unstructured data. - Optimize and manage SQL queries for performance and efficiency in large-scale datasets. - Collaborate with data scientists, analysts, and business stakeholders to translate requirements into technical solutions. - Experience in implementing solutions for streaming data (e.g., Apache Kafka, AWS Kinesis) is preferred but not mandatory. - Ensure data quality, governance, and security across pipelines and storage systems. - Document architectures, processes, and workflows for clarity and reproducibility. Requirements: - 4 or more years of experience in Data Engineering. - Expertise in SQL (complex queries, optimization, and database design). - Solid understanding and hands-on experience in creating data pipelines and patterns. - Proficiency in programming languages like Python or R for scripting, automation, and pipeline development. - Hands-on experience with Google BigQuery and Apache Airflow. - Experience working on cloud-based platforms like AWS, GCP, or Azure. - Familiarity with structured data (RDBMS) and unstructured data (JSON, Parquet, Avro). - Knowledge of cloud-based data warehouses (Redshift, BigQuery, Snowflake). - Familiarity with version control systems (e.g., Git) and CI/CD practices.