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Job Summary

The Senior Data Engineer is responsible for designing, developing, implementing, and maintaining scalable data solutions that enable data-driven decision-making across the organization. This role serves as a technical leader in the design and optimization of enterprise data platforms, data pipelines, and data integration frameworks. The Senior Data Engineer collaborates closely with business stakeholders, product owners, analysts, and technology teams to translate business requirements into robust data architectures, high-quality datasets, and reporting solutions.

The individual will lead the development of data engineering best practices, ensure data quality and governance standards are met, and support enterprise reporting, analytics, automation, and operational initiatives. This role requires deep expertise in cloud-based data platforms, data warehousing, ETL/ELT development, data modeling, and enterprise application integrations. The position will also play a key role in enabling data accessibility, reliability, and scalability across multiple business functions.

Primary Duties May Include, But Are Not Limited To:

·    Design, develop, and maintain scalable data pipelines and integration solutions supporting enterprise reporting, analytics, and operational processes.

·    Build and optimize ETL/ELT workflows to ingest, transform, validate, and load data from multiple internal and external source systems.

·    Develop and maintain enterprise data warehouse structures, data marts, and analytical datasets.

·    Design and implement logical and physical data models that support business intelligence, reporting, and advanced analytics requirements.

·    Integrate data from APIs, enterprise applications, flat files, connectors, and scheduled data feeds.

·    Collaborate with business stakeholders, product teams, and analysts to understand business needs and translate requirements into technical solutions.

·    Establish and maintain data quality controls, validation processes, and monitoring mechanisms to ensure data accuracy and integrity.

·    Create and maintain metadata, data dictionaries, lineage documentation, and technical specifications.

·    Optimize database performance, query efficiency, and data processing capabilities within cloud and on-premises environments.

·    Support the implementation and administration of enterprise work management and workflow platforms, including integration with data repositories and reporting solutions.

·    Develop reusable frameworks, standards, and best practices for data engineering and data management.

·    Partner with data analysts, business intelligence developers, and solution architects to enable scalable reporting and self-service analytics capabilities.

·    Troubleshoot data integration issues, perform root cause analysis, and implement sustainable solutions.

·    Support data governance, compliance, security, and privacy requirements through appropriate controls and technical design.

·    Mentor junior data engineers and provide technical leadership on complex data initiatives and enterprise projects.