CES - Data Engineer - Python/SQL/ETL

Role : Data Engineer

About the Role:

We are looking for an experienced Data Engineer with 7 - 12 years of hands-on experience in designing, developing, and maintaining scalable data pipelines and data platforms. The ideal candidate should have strong expertise in data engineering concepts, SQL, Python, ETL/ELT processes, and cloud-based data technologies.

Key Responsibilities:

• Design, develop, and maintain scalable and reliable data pipelines for processing large volumes of structured and unstructured data.
• Build and optimize ETL/ELT workflows to ingest, transform, and load data from multiple sources.
• Develop efficient and complex SQL queries for data extraction, transformation, validation, and analysis.
• Develop data processing solutions using Python and other relevant programming technologies.
• Design and maintain data models, data warehouses, and data marts to support business and analytical requirements.
• Work with cross-functional teams to understand business requirements and translate them into scalable data solutions.
• Implement data quality, validation, reconciliation, and monitoring processes.
• Optimize data pipelines and queries for improved performance and scalability.
• Work with cloud-based data platforms and services to build modern data engineering solutions.
• Troubleshoot data pipeline failures and production issues and perform root-cause analysis.
• Ensure data security, governance, availability, and reliability across data platforms.
• Participate in code reviews and follow established development and engineering best practices.
• Create and maintain technical documentation for data pipelines, workflows, and architecture.
• Collaborate with Data Scientists, Analysts, BI teams, and other stakeholders to enable data-driven solutions.
• Contribute to the design and implementation of scalable data architecture and engineering standards.

Required Skills:

• 7 - 12 years of relevant experience in Data Engineering.
• Strong proficiency in SQL and database concepts.
• Strong hands-on experience with Python.
• Experience building and managing ETL/ELT pipelines.
• Strong understanding of data warehousing, data modelling, and data integration.
• Experience working with large-scale data processing and distributed data systems.
• Good understanding of cloud data platforms such as AWS, Azure, or GCP.
• Experience with data orchestration/workflow tools such as Airflow or equivalent.
• Knowledge of data quality, governance, and security practices.
• Strong troubleshooting and problem-solving skills.
• Good communication and stakeholder management skills.

Tech Stack:

Data Engineering, Python, SQL, ETL/ELT, Data Pipelines, Data Warehousing, Data Modelling, Cloud, Airflow, Data Integration, Data Quality