数据与集成工程师

With this expansion, Peak Energy is searching for a Data & Integration Engineer to build, operate, and continuously improve the governed data pipelines and data products that connect Peak Energy's core business systems.

The role will work across data sources from enterprise applications to create a centralized data platform for analytics, reporting, automation, and AI use cases. The role combines hands-on data engineering with data quality, integration, testing, observability, documentation, and practical collaboration with business and technology stakeholders.

Main Responsibilities

Microsoft Fabric & Data Engineering

• Build and operate ingestion and transformation pipelines using Microsoft Fabric Data Factory, notebooks, SQL, Python, and Spark.
• Implement and maintain governed Bronze, Silver, and Gold data layers in OneLake/Lakehouse, with clear transformation logic and reusable patterns.
• Develop reliable batch and API-based ingestion from enterprise applications.
• Optimize pipelines and notebooks for maintainability, performance, recoverability, and controlled production operation.
• Support environment configuration, deployment, scheduling, monitoring, and operational troubleshooting for the data platform.

Data Integration, Quality & Reconciliation

• Design and implement mappings, transformations, identifiers, and validation rules that connect project, financial, commercial, and other enterprise data.
• Build automated data-quality checks, reconciliation controls, exception reporting, and traceable remediation processes.
• Work with application owners and business stakeholders to investigate source-data issues and establish clear ownership for correction.
• Develop and maintain REST API integrations and approved file-based interfaces where required, applying secure and supportable integration patterns.
• Support testing of integrations between enterprise applications, Microsoft Fabric, and reporting or workflow solutions.

Analytics Data Products & Governance

• Create curated data products and dimensional models that support Power BI, operational reporting, project analytics, and approved AI use cases.
• Prepare clean and well-structured datasets for semantic models, dashboards, reconciliation reporting, and downstream analytical consumption.
• Maintain technical metadata, lineage, data definitions, transformation documentation, and operating procedures in coordination with data governance owners.
• Partner with architecture and security stakeholders to apply approved access, retention, privacy, and data-protection requirements.
• Support Microsoft Purview lineage and cataloguing activities for the data products and pipelines within the role's scope.

Engineering Practices & Service Ownership

• Apply source control, CI/CD, peer review, testing, release management, and documented rollback practices to production data solutions.
• Implement logging, alerting, observability, and support procedures for recurring data pipelines and integration services.
• Produce clear technical documentation, runbooks, data mappings, test evidence, and handover materials.
• Work effectively with Microsoft specialists, implementation partners, and application vendors while retaining internal knowledge and operational ownership.
• Contribute to the technical acceptance of externally delivered data components and continuously reduce avoidable manual support and consultant dependency.

Qualifications

• Bachelor's degree in Computer Science, Data Engineering, Information Technology, Information Systems, Engineering, or a related field.
• Approximately 4-7 years of relevant experience in data engineering, analytics engineering, enterprise integration, or data-platform delivery.
• Hands-on experience with Microsoft Fabric Data Factory, Fabric Lakehouse/OneLake, notebooks, SQL, Python, and Spark is strongly preferred.
• Practical experience designing and supporting ETL/ELT pipelines, REST API integrations, data models, data-quality controls, and reconciliation processes.
• Working knowledge of medallion architecture, dimensional modelling, semantic-model preparation, metadata management, lineage, and data governance.
• Experience with Git-based source control, CI/CD, automated testing, monitoring, and production support for data solutions.
• Microsoft certifications in Fabric, Azure data services, Power BI, or related technologies are a strong advantage.
• Experience with Microsoft Purview and Power BI is an advantage.
• Experience with Microsoft Dynamics 365 Business Central, Salesforce, or finance data is an advantage.