Job Description
Job DescriptionWe are looking for a skilled Data Engineer to design, develop, and maintain data systems that support critical business operations and analytics. This role requires collaboration with various teams to ensure data integrity, reliability, and scalability. You will play a pivotal role in optimizing data workflows and implementing robust solutions to meet organizational needs.
Responsibilities:
• Develop and maintain scalable data pipelines to integrate information from various sources.
• Create and manage data models, tables, and warehouses using platforms such as Redshift, BigQuery, or Snowflake.
• Implement automated workflows and data quality checks to guarantee accurate and consistent datasets.
• Collaborate with cross-functional teams to understand and address their data requirements.
• Enhance query efficiency by applying techniques such as indexing, partitioning, and dataset restructuring.
• Ensure adherence to best practices in data governance, security, and comprehensive documentation.
• Troubleshoot and resolve issues related to data pipelines and infrastructure.
• Incorporate tools like Airflow, dbt, or Kafka to streamline data processing and management.
• Support real-time data processing and streaming initiatives.
• Facilitate the integration of DevOps tools like Docker, Terraform, or CI/CD pipelines into data systems.• A minimum of 3–7 years of experience in a Data Engineering role or equivalent.
• Proficiency in programming languages such as Python or other scripting tools.
• Demonstrated expertise in cloud-based data platforms such as AWS, Google Cloud, or Azure.
• Solid understanding of ETL processes, data modeling, and distributed systems.
• Familiarity with data pipeline tools like Airflow, dbt, or Kafka.
• Strong problem-solving skills to address data issues and optimize performance.
• Knowledge of Apache Spark, Hadoop, and Kafka.
• Experience with BI tools like Tableau, Power BI, or Looker is a plus.