Azure Data Integration Engineer

Rate: up to 170 pln/h on b2b

Location: 100% remotely

Summary: As a Data Integration Engineer, your primary objective is to design, build, and operate robust data integration solutions within an agile, DevOps-focused team operating in Azure Cloud. This role emphasizes creating seamless connections among various applications, services, and data streams, ultimately supporting data-driven decision-making.

Main Responsibilities:

• Build and operate integration solutions using Azure services and messaging technologies.

• Design and maintain workflows with DAG-based orchestration frameworks (e.g., Argo Workflows).

• Develop data pipelines connecting various data sources through Azure Data Factory and Databricks.

• Write efficient SQL for data extraction, validation, and transformation.

• Collaborate with cross-functional teams to translate integration needs into technical solutions.

• Advise on integration patterns and architecture in clear, digestible terms for non-technical stakeholders.

• Engage in DevOps practices, including automated deployments and infrastructure-as-code.

• Contribute actively within an agile Scrum team environment.

Key Requirements:

• Solid background in Azure Cloud, especially in integration, messaging, and data workloads.

• Hands-on experience with Azure Data Factory for source connectivity and pipeline orchestration, and with Databricks (PySpark, Delta Lake) for data transformation and enrichment.

• Strong SQL skills and solid database know-how; experience working with enterprise systems and databases such as SAP and DB2 is a plus.

• Experience with workflow orchestration systems (e.g., Argo Workflows, Temporal, Airflow) and DAG-based integration patterns.

• Good understanding of API concepts (e.g. REST) and experience consuming APIs as a data source.

• Experience with Kubernetes (AKS preferred), containerized applications, and cloud-native architecture.

• Experience with integration & messaging technologies such as Azure Service Bus, Kafka, Event Hub, or similar.

• Strong knowledge of Python for scripting, data pipeline development, and automation; basic understanding of Java for working with existing components.

• Familiarity with DevOps practices and toolchains (CI/CD, IaC, monitoring, GitOps, etc.).

• Ability to communicate technical topics clearly to stakeholders at different levels.

• A consultative mindset and team-player attitude.

Nice to Have:

• Experience in data-heavy sectors like finance or logistics.

• Experience with both SQL and NoSQL databases.