Data Engineer — AMK
Must-have:PythonCloudDataCI/CDFinTechSecurity
Job Responsibilities
- Analyse and migrate existing workflow integrations to new platforms.
- Develop workflow orchestration, including triggers, routing, retries and exception handling.
- Build automation for batching, pagination, looping and throttling.
- Design and maintain ETL pipelines for file-based data ingestion into relational databases.
- Perform schema validation, data quality checks and error reconciliation.
- Develop data pipelines using cloud-based big data platforms and distributed processing frameworks such as Spark.
- Support Lakehouse-based data environments for batch and streaming workloads.
- Implement logging, monitoring and alerting for data pipelines and workflows.
- Troubleshoot issues and participate in root-cause analysis and continuous improvement.
- Work with application teams to understand data requirements and upstream/downstream dependencies.
- Ensure data pipelines meet performance, reliability, security and governance requirements.
Job Requirements
- 3–5 years of relevant experience in Data Engineering, Integration Engineering or a related role.
- Experience with workflow orchestration or integration platforms .
- Hands-on experience with ETL and file-based data ingestion.
- Proficient in SQL and relational databases such as SQL Server .
- Experience with Spark or other distributed data processing frameworks.
- Experience with Python or other programming/scripting languages.
- Understanding of batch and streaming data processing .
- Experience with cloud platforms and managed data services .
- Experience working with REST APIs, JSON and CSV .
- Understanding of CI/CD for data and integration workflows.
- Good understanding of data quality, error handling and pipeline reliability.
Good to Have
- Experience with Lakehouse table formats , incremental processing and time travel.
- Experience with Flink or Spark Streaming .
- Familiarity with analytical query engines.
- Experience in banking, financial services, manufacturing or other regulated environments.
- Knowledge of data observability and data quality tools.