Data Engineer

Job Title: Senior Data Engineer Location: Glendale, California, USA Job Type: Full-Time Experience: 9–13 Years Domain: Information Technology (IT) Job Summary We are seeking an experienced Senior Data Engineer to design, develop, and optimize scalable data solutions that support business intelligence, analytics, and enterprise data initiatives. The ideal candidate will have strong expertise in data engineering, cloud platforms, ETL/ELT pipelines, data modeling, and big data technologies. This role requires collaboration with data analysts, architects, business teams, and engineering teams to deliver reliable and high-performance data solutions. Key Responsibilities Design, develop, and maintain scalable data pipelines and ETL/ELT processes. Build and optimize data platforms, data warehouses, and data lakes. Develop data integration solutions using batch and real-time processing frameworks. Perform data modeling, transformation, cleansing, and validation activities. Collaborate with business stakeholders and data analysts to understand data requirements. Implement solutions using cloud-based data technologies and modern data architectures. Optimize SQL queries, data processing jobs, and system performance. Ensure data quality, security, governance, and compliance standards. Troubleshoot complex data issues and provide root cause analysis. Develop and maintain technical documentation for data solutions. Participate in Agile ceremonies, design discussions, and code reviews. Mentor junior engineers and contribute to best practices within the data engineering team. Required Qualifications Bachelor’s degree in Computer Science, Information Technology, Engineering, or related field. 9–13 years of experience in Data Engineering, ETL development, and enterprise data solutions. Strong programming experience with Python, SQL, and data processing frameworks. Hands‑on experience designing and developing ETL/ELT pipelines. Strong experience with data warehousing concepts, data modeling, and database technologies. Experience working with cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP). Experience with big data technologies and distributed processing systems. Strong analytical, problem‑solving, and communication skills. Preferred Skills Experience with Apache Spark, Hadoop, Kafka, Databricks, or Snowflake. Experience with cloud data services such as AWS Glue, Azure Data Factory, BigQuery, or similar platforms. Knowledge of data lake, lakehouse, and modern data architecture patterns. Experience with CI/CD, DevOps practices, and automation. Familiarity with data governance, metadata management, and data quality frameworks. Experience working in Agile/Scrum environments. Technical Skills Python SQL ETL / ELT Development Data Warehousing Data Modeling Data Lakes Apache Spark Databricks Snowflake Hadoop Kafka Cloud Platforms (AWS/Azure/GCP) Azure Data Factory / AWS Glue Database Technologies API Integration Git CI/CD Pipelines Agile/Scrum #J-18808-Ljbffr