ETL Python

As a Data Engineer, you will be responsible for designing, building, and maintaining data pipelines to ensure data quality and reliability. Your main tasks will include data cleansing, imputation, mapping to standard data models, transforming data to meet business rules and statistical computations, and validating data content. You will be developing, modifying, and maintaining Python and Unix scripts, as well as complex SQL queries. Performance tuning of existing code to enhance efficiency and avoid bottlenecks will be a key part of your role. Building end-to-end data flows from various sources to curated and enhanced datasets will be crucial. Additionally, you will develop automated Python jobs for data ingestion and provide technical expertise in architecture, design, and implementation. Collaborating with team members, you will create insightful reports and dashboards to improve processes and add value. SQL query writing for data validation and designing ETL processes for data extraction, transformation, and loading will also be part of your responsibilities. You will work closely with data architects, analysts, and stakeholders to understand data requirements and ensure data quality. Optimizing and tuning ETL processes for performance and scalability will be essential. Maintaining documentation for ETL processes, data flows, and mappings, as well as monitoring and troubleshooting ETL processes to ensure data accuracy and availability, will be key responsibilities. Implementing data validation and error handling mechanisms to maintain data integrity and consistency will also be part of your role. Required Skills: - Python - ETL Tools like Informatica, Talend, SSIS, or similar - SQL, MySQL - Expertise in Oracle, SQL Server, and Teradata - DevOps, GitLab - Experience in AWS Glue or Azure Data Factory If you are passionate about data engineering and have the skills mentioned above, we would love to have you on our team!,