Python - Data Processing

Responsibilities :

Key Responsibilities:

Build and maintain Python-based data processing components for structured and semi-structured datasets.

Develop and support ETL workflows to ingest, transform, validate, and load data into target systems.

Design and optimize SQL queries for data extraction, transformation, reconciliation, and reporting needs.

Implement reliable data pipelines with proper logging, error handling, retries, and monitoring hooks.

Perform data quality checks, anomaly detection rules, and reconciliation to ensure accuracy and completeness.

Troubleshoot pipeline failures and performance bottlenecks drive root-cause analysis and permanent fixes.

Collaborate with cross-functional teams to gather requirements and deliver incremental improvements.

Maintain clear technical documentation for pipeline design, data mappings, and operational runbooks.

Additional Responsibilities:

Minimum Qualifications:

Bachelor's degree (or equivalent) in Engineering/Computer Science/IT or related field (BTech/BE/BSc or equivalent).

2-3 years of hands-on experience in Python for data processing and automation.

Practical experience building ETL processes and working with data pipelines end-to-end.

Strong SQL skills including joins, aggregations, subqueries, and performance-aware query writing.

Ability to write clean, maintainable code and follow basic engineering practices (version control, reviews, testing mindset). Preferred Qualifications:

Experience designing scalable pipeline patterns (incremental loads, CDC concepts, partitioning, backfills).

Familiarity with Python data libraries and processing approaches (e.g., Pandas, batch processing patterns).

Exposure to orchestration/scheduling concepts and operationalizing pipelines for reliability and observability.

Experience working with large datasets and optimizing end-to-end pipeline performance (I/O, SQL tuning, compute efficiency).

Proven ability to collaborate with stakeholders, translate requirements into technical solutions, and deliver within timelines. Good to have skills: Pandas, NumPy, Apache Airflow, Spark (PySpark), Linux/Shell Scripting

Technical and Professional Requirements:

Primary skills: Python - Data Processing/Technology- Big Data - Data Processing- PySpark,Technology- OpenSystem- Python - OpenSystem- Python