Data Engineer (ETL/ELT) (Finance Domain)

Key Responsibilities: • Develop and maintain data pipelines and ETL/ELT/analytics engineering workflows to support advanced search and retrieval capabilities. • Collaborate with data teams to understand requirements and automate deployment and monitoring. • Optimize data storage and troubleshoot issues to enhance performance. • Work closely with data engineers and relevant parties to ensure sprints are planned out properly and completed timely. • Perform BAU monitoring, investigations and resolutions. • Assist with data governance and data management initiatives. • Production and application support from a day-to-day basis. Skillset Requirements • Possess a degree in Computer Science/Information Technology or related fields. • At least 5 years of hands-on experience in software or data engineering with proficiency in Python. • Strong experience in unit and integration testing. • Familiarity with DevOps practices and Agile methodologies. • Experience with AWS and Kubernetes (K8s). • Familiarity with data platforms such as Snowflake, Databricks, Apache Spark, Apache Hive, open table formats (Delta Lake, Apache Iceberg), and vector databases. • Experience with orchestration tools such as Apache Airflow, Dagster, Prefect, and Temporal. • Familiarity with GitHub workflows and Datadog. • Good written and verbal communication skills. • Agile, fast learner and able to adapt to changes.