Data Platform Engineer

Role Overview We are looking for an experienced Data Platform Engineer to support the development and operations of Data Warehouse . The role will focus on building and maintaining scalable data pipelines, ETL/ELT workflows, data platforms, and analytics engineering solutions, while providing ongoing production and application support. Key Responsibilities • Develop and maintain data pipelines, ETL/ELT processes, and analytics engineering workflows to support advanced data search and retrieval. • Collaborate with data and engineering teams to understand requirements and automate deployment, monitoring, and operational processes . • Optimise data storage, processing, and query performance while troubleshooting technical issues. • Coordinate with data engineers and stakeholders to support sprint planning and timely delivery . • Perform BAU monitoring, investigation, troubleshooting, and incident resolution . • Support data governance and data management initiatives. • Provide day-to-day production and application support , ensuring platform stability and reliability. • Develop and maintain unit and integration tests to ensure data and application quality. Requirements • Degree in Computer Science, Information Technology , or a related discipline. • At least 5 years of hands-on Software Engineering or Data Engineering experience . • Strong programming experience in Python and ETL • Strong experience with unit and integration testing . • Experience with AWS and Kubernetes (K8s) . • Familiarity with modern data platforms and technologies such as Snowflake, Databricks, Apache Spark, Apache Hive, Delta Lake, Apache Iceberg, and vector databases . • Experience with workflow/orchestration technologies such as Apache Airflow, Dagster, Prefect, or Temporal . • Familiarity with GitHub workflows, Datadog, DevOps practices, and Agile methodologies . • Good analytical, troubleshooting, communication, and collaboration skills. Key Technologies Python | AWS | Kubernetes | Snowflake | Databricks | Apache Spark | Apache Hive | Delta Lake | Apache Iceberg | Vector Databases | Airflow | Dagster | Prefect | Temporal | GitHub | Datadog | ETL/ELT