Senior Data Engineer

• Analyze, maintain, and optimize existing Python scripts to ensure seamless data pipeline automation and system reliability.
• Design and implement scalable processes to transform unstructured or semi-structured data like JSON, XML, and logs into structured tabular formats.
• Develop and manage end-to-end ETL and CDC workflows using tools such as SSIS, Talend, Informatica, or Azure Data Factory.
• Implement event-based streaming and real-time data processing using Debezium, Kafka, Flink, and Spark.
• Manage and query diverse database environments, including PostgreSQL, Oracle, SQL Server, NoSQL (MongoDB), and GraphDB (Gsql/TG).
• Oversee Data Warehouse architecture and manage job scheduling and orchestration across cloud (GCP/BigQuery/Azure) and on-premise systems.
• Collaborate with cross-functional teams to translate complex data requirements into technical solutions while troubleshooting and resolving pipeline issues.

Qualifications:

• At least 5-8 years of professional work experience, with a heavy specialization in Data Engineering. Hands-on experience with SQL, focusing on performance tuning, complex joins, and data granularity.
• Strong proficiency in Python, specifically the ability to read, refactor, and maintain existing codebases.
• Proven expertise in ETL tools (Kettle, Pentaho, Informatica) and modern data transformation frameworks like dbt (data build tool).
• Knowledge of Big Data tools such as Hive, Impala, and cloud-native solutions like BigQuery and Azure Data Factory.
• Familiarity with REST APIs, basic programming principles, and data visualization tools like Power BI.
• Proactive mindset with an eagerness to learn and adapt to new emerging technologies.