Data Engineer

We are seeking an experienced Data Engineer to architect, build, and optimize scalable data pipelines and cloud-based data platforms that support advanced analytics, reporting, and business intelligence initiatives.

Responsibilities

• Design, develop, and maintain robust ETL/ELT pipelines for ingesting, transforming, and loading structured and semi-structured data.
• Build and manage scalable data pipelines using Python and SQL across cloud and warehouse environments.
• Optimize data storage, query performance, and overall efficiency within modern data warehouse platforms.
• Develop and maintain data models that support downstream analytics, reporting, and operational use cases.
• Collaborate with business stakeholders, analysts, and engineering teams to define data requirements and translate them into technical solutions.
• Implement and support data quality checks, governance standards, and monitoring processes to ensure data reliability and integrity.
• Troubleshoot pipeline failures, performance bottlenecks, and data consistency issues across the data ecosystem.
• Contribute to best practices in data architecture, orchestration, documentation, and deployment.
• 4+ years of hands-on experience in data engineering or a related field.
• Strong proficiency in Python and advanced SQL for data transformation, automation, and performance tuning.
• Experience with modern cloud data tools and platforms such as Azure Data Factory, Snowflake, Databricks, or AWS-based data services.
• Solid understanding of data modeling, data warehousing, and ETL/ELT design principles.
• Experience working with large-scale datasets and building reliable, production-grade data solutions.
• Familiarity with data governance, data validation, and pipeline orchestration best practices.