Etl Developer

Role & responsibilities

• Design, develop, and maintain ETL pipelines to extract, transform, and load data from various sources into Oracle, Snowflake, or cloud data warehouses.
• Write and optimize PL/SQL scripts, stored procedures, and functions for data processing and performance tuning.
• Build and configure Talend jobs (or other ETL tools) for batch and real-time data integration.
• Develop and support data models, schemas, and warehouse structures aligned with business reporting needs.
• Collaborate with BI teams to enable dashboards and reports in Cognos and Power BI.
• Implement data quality checks, validations, and reconciliation mechanisms.
• Work with cloud data platforms (AWS, Azure, or GCP) for scalable ETL and storage solutions.
• Apply best practices in ETL job scheduling, error handling, logging, and performance optimization.
• Support end-to-end data lifecycle from ingestion to consumption, ensuring governance and compliance.
• Document ETL designs, data flows, and technical specifications for knowledge sharing.

Preferred candidate profile

• Bachelor's or Master's degree in Computer Science, Information Systems, or related field.
• 3-8 years of hands-on ETL development experience.
• Strong expertise in Oracle SQL, PL/SQL, and database optimization.
• Hands-on experience with ETL tools such as Talend (preferred), Informatica, or equivalent.
• Proficiency in Snowflake (warehousing, pipelines, SnowSQL, performance tuning).
• Good understanding of BI tools: Cognos, Power BI (data modeling, DAX, visualization best practices).
• Solid experience with cloud services (AWS Redshift/Glue, Azure Data Factory/Synapse, GCP BigQuery/Dataflow).
• Knowledge of data modeling concepts (star/snowflake schema, normalization, dimensional modeling).
• Experience with job orchestration & scheduling tools (Control-M, Autosys, Airflow, or similar).
• Strong understanding of data quality frameworks, metadata management, and error handling.
• Exposure to CI/CD pipelines, Git, Jenkins, and version control practices for ETL jobs.
• Knowledge of Python or Shell scripting for automation and custom transformations.
• Familiarity with real-time streaming (Kafka, Spark Streaming, Kinesis, or Pub/Sub).
• Basic knowledge of API-based integrations (REST, SOAP).