Data Engineer (Denado)

Requirements

• Minimum 3 years of experience as a Data Engineer, ETL Developer, or in a similar data engineering role.
• Strong SQL skills and experience with relational databases such as Oracle, PostgreSQL, MySQL, or similar.
• Proficient in Python for data processing, automation, and scripting.
• Hands-on experience in developing and maintaining ETL/ELT pipelines and data integration processes.
• Good understanding of Data Warehouse concepts, data modeling, and data pipeline architecture.
• Experience in query optimization, performance tuning, and troubleshooting data processing jobs.
• Familiar with Linux/Unix environments and Git version control.
• Experience with data quality, data validation, reconciliation, and data transformation.
• Good analytical and problem-solving skills.
• Good communication skills and ability to collaborate with both technical and business stakeholders.
• Experience with Spark/PySpark, Kafka, Airflow, Dataiku, or cloud platforms is a plus.
• Experience in regulatory reporting, financial data, or banking projects is a plus.

Responsibilities

• Design, develop, and maintain ETL/ELT pipelines and data processing workflows.
• Develop and maintain Data Warehouse solutions, data models, and reporting datasets.
• Integrate data from multiple sources and ensure data accuracy, consistency, and reliability.
• Develop Python scripts and automation solutions for data processing and operational tasks.
• Develop and optimize SQL queries, database processes, and ETL jobs.
• Perform data validation, reconciliation, and data quality checks.
• Troubleshoot data pipeline, data quality, and performance issues.
• Monitor and improve the performance, reliability, and scalability of data pipelines.
• Collaborate with Data Analysts, Business Users, Software Engineers, and other stakeholders to deliver data solutions.
• Support data migration, system integration, and other data engineering initiatives.
• Maintain technical documentation for data pipelines, data models, and processes.
• Follow best practices for development, testing, deployment, monitoring, and version control.
• Contribute to improvements in data architecture and data engineering practices.

Skills: Data Engineering, ETL, Data Integration, Python, MongoDB, Redis, Hadoop, Data Processing, Denado, Database Systems, Microsoft SQL Server