Python Developer

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Job Title: Data Engineer (Python / Oracle)

We are looking for a Data Engineer with strong expertise in Python, Oracle Database, and data pipeline development.

Key Responsibilities:
• Design and develop scalable ETL/ELT data pipelines using Python
• Work with Oracle Database for SQL/PLSQL development and performance tuning
• Build and optimize data models for OLTP and OLAP systems
• Develop data integration solutions using tools like Airflow, Kafka, and PySpark
• Ensure data quality, validation, and governance standards
• Monitor and troubleshoot data pipelines and database performance
• Work in CI/CD environment using Git, Jenkins, and GitHub Actions

Required Skills:

• Programming & Scripting (Primary)

• Advanced Python (3.x) OOP, typing, async, performance profiling
• Familiarity with Python dataengineer libraries: pandas, pyarrow, sqlalchemy, cx_Oracle, oracledb,polars, duckdb

• Shell scripting (bash, PowerShell) for automation and orchestration

• Oracle Database Expertise (Primary)

• Oracle Database (11g/12c/19c/21c) administration basics
• SQL proficiency: complex queries, analytic functions, hierarchical queries, PL/SQL development
• Data modeling (ER, dimensional) and schema design for OLTP & OLAP
• Performance tuning: indexing, partitioning, optimizer hints, AWR/ASH analysis

• Oracle Data Pump, SQL*Loader, External Tables

• Data Integration & ETL (Primary)

• Design and implementation of ETL/ELT pipelines in Python (e.g., polars,pandas, pySpark, dbt)
• Knowledge of messaging/streaming (Kafka, RabbitMQ) for realtime ingestion

• Data orchestration platforms: Apache Airflow, Prefect, or Azure Data Factory

• Big Data & Distributed Processing (Secondary)

• Working knowledge of Apache Spark (PySpark) and its integration with Oracle

• Experience with cloudbased bigdata services (AWS EMR, Azure Synapse, GCP Dataproc)

• Cloud & DevOps (Secondary)

• Oracle Cloud Infrastructure (OCI) services: Autonomous DB, Object Storage, Functions
• Containerization (Docker) and orchestration (Kubernetes) for scalable pipelines
• CI/CD pipelines (Git, Jenkins, GitHub Actions) for automated testing and deployment

• InfrastructureasCode tools (Terraform, OCI Resource Manager)

• Data Quality & Governance (Primary)

• Implementing data validation, profiling, and cleansing in Python
• Familiarity with data lineage, metadata management, and catalog tools (Apache Atlas, Collibra)

• Understanding of GDPR, CCPA, and other dataprivacy regulations

• Testing & Monitoring (Primary)

• Unit & integration testing frameworks (pytest, unittest) for data pipelines

• Monitoring & alerting (Prometheus, Grafana, OCI Monitoring) of ETL jobs and database health

• Version Control & Collaboration (Secondary)

• Proficient with Git (branching, pullrequests, code reviews)
• Agile methodologies (Scrum/Kanban) and ticketing systems (Jira, Azure Boards)