Python Data Automation Engineer

Job Description Python Data Automation Engineer

Experience: 5–12 Years
Location:Bangalore
Employment Type: Full-Time
Role: Python Data Automation Engineer

Job Summary

We are looking for an experienced Python Data Automation Engineer to design, develop, and automate data pipelines for enterprise data platforms. The ideal candidate should have strong hands-on experience with Python, SQL, Airflow, and data engineering, along with a good understanding of data validation, reconciliation, monitoring, and data quality.

The candidate will work on building reliable and scalable data automation solutions and integrating data across databases, APIs, and modern data platforms.

Key Responsibilities

• Develop and maintain Python-based data pipelines and automation frameworks.
• Integrate Python applications with databases, data platforms, APIs, and external systems.
• Design data validation, reconciliation, and monitoring processes.
• Develop and manage workflows using Apache Airflow.
• Build automated data quality checks and validation mechanisms.
• Monitor data pipelines and troubleshoot failures or data issues.
• Ensure data pipelines are scalable, reliable, and performance optimized.
• Write efficient and complex SQL queries for data extraction and validation.
• Work with enterprise data platforms and databases.
• Develop reusable Python modules and automation utilities.
• Analyze data discrepancies and perform root-cause analysis.
• Work with cross-functional teams including Data Engineers, Developers, QA, and Business teams.
• Follow coding standards, version control, testing, and deployment practices.
• Work in Linux/Unix environments for development, automation, and troubleshooting.

Required Skills

• 5–12 years of experience in Data Engineering, Data Automation, or a related field.
• Strong hands-on experience with Python in a data engineering/automation environment.
• Strong knowledge of SQL and database concepts.
• Hands-on experience with Apache Airflow or similar workflow orchestration tools.
• Experience developing ETL/ELT data pipelines.
• Experience with data validation, reconciliation, and data quality processes.
• Experience integrating data through APIs and databases.
• Good understanding of data pipeline monitoring and troubleshooting.
• Working knowledge of Linux/Unix.
• Strong problem-solving and analytical skills.

Good to Have

• Experience with Snowflake.
• Exposure to Big Data technologies such as Spark, Hadoop, or Databricks.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Knowledge of Git and CI/CD practices.
• Experience with data quality or data observability tools.
• Experience working with large-scale enterprise data platforms.