Data Engineer

Job summary

POSITION SUMMARY The Data Engineer designs, builds, and maintains scalable data solutions that support operational reporting, analytics, and enterprise decision-making. This role is responsible for developing reliable data pipelines, integrating data from internal and third-party systems, and delivering trusted, well-structured data for business use across the organization.

Benefits

Qualifications

• by applying access controls, audit practices, retention standards, and secure data handling procedures.
• Collaborate with business stakeholders, analysts, developers, and IT team members to gather
• define technical approaches, and deliver high-value data solutions.
• Create and maintain technical documentation for pipelines, source mappings, transformations, data definitions, standards, and operational procedures.
• Participate in troubleshooting, root cause analysis, and continuous improvement efforts related to data platform health, performance, and service reliability.
• Contribute to standards for version control, testing, deployment, and change management for data assets and engineering workflows.
• Perform additional
• to make informed technical decisions.
• Diagnose and resolve data issues using sound logic and reasoning, including query inefficiencies, data integrity concerns, and platform-related bottlenecks.
• Anticipate potential risks and take proactive steps to improve resilience, scalability, and operational continuity.
• INITIATIVE AND ADAPTABILITY
• Take initiative when operational challenges or opportunities for improvement arise, acting decisively while protecting data availability and integrity.

Responsibilities

• This role is responsible for developing reliable data pipelines, integrating data from internal and third-party systems, and delivering trusted, well-structured data for business use across the organization.
• Design, build, and maintain scalable data pipelines and data integration processes that move data reliably from source systems into curated analytical and operational data stores.
• Develop ETL/ELT workflows for structured, semi-structured, and file-based data using appropriate orchestration, transformation, and scheduling methods.
• Implement and support Microsoft Fabric solutions, including Data Factory pipelines, Lakehouse, Warehouse, Dataflow Gen2, notebooks, and related services for ingestion, transformation, and delivery of trusted data.
• Design and maintain data models, schemas, and data structures that support reporting, analytics, and downstream application needs.
• Integrate data from enterprise applications, databases, APIs, flat files, and third-party platforms while ensuring data accuracy, completeness, and consistency.
• Optimize data queries, transformation logic, storage design, and pipeline performance to improve reliability, scalability, and cost efficiency.
• Implement monitoring, alerting, logging, and data quality checks to detect failures, anomalies, and processing issues before they affect business operations.
• Support data governance, security, and compliance
• as assigned in support of evolving business priorities and enterprise data initiatives.
• EFFECTIVENESS AND WORK MANAGEMENT
• To perform successfully in this role, the following

Skills

Degrees

Work schedule

Industry

Company size

Contract length