Senior Data Engineer

About the role

The Banner is seeking an experienced and hands-on Senior Data Engineer to help scale and mature our modern cloud-based data platform as we expand operations through the acquisition and integration of the Pittsburgh Post-Gazette. This is a high-impact role focused on building scalable data pipelines, establishing strong data governance and engineering practices, and enabling trusted analytics across editorial, subscriptions, audience engagement, advertising, philanthropy, finance, and operations. You will play a critical role in consolidating fragmented reporting systems into a centralized, cloud-native data ecosystem. Your work will help leaders and teams make faster, more informed decisions through reliable, accessible, and well-governed data. The ideal candidate is both a strong technical engineer and a pragmatic systems thinker. You are comfortable working across business and technical teams, designing sustainable data foundations, and solving complex problems in a fast-moving digital media environment.

Responsibilities

• Data Platform and Pipeline Engineering
• Design, build, and maintain scalable batch and near-real-time data pipelines on AWS.
• Develop robust ETL and ELT workflows that integrate data from multiple operational systems.
• Expand and evolve our existing AWS-based data lake architecture to support multi-organization analytics and reporting.
• Standardize ingestion, transformation, modeling, and serving layers across acquired systems and platforms.
• Contribute to architecture decisions and long-term data platform strategy.
• Build reliable, reusable, and well-documented data assets that support analytics, reporting, and operational decision-making.
• Acquisition and Systems Integration
• Lead data integration work related to Pittsburgh Post-Gazette systems and reporting infrastructure.
• Centralize fragmented reporting pipelines and migrate ad hoc reporting processes into governed, enterprise-grade workflows.
• Create scalable mechanisms for aligning KPIs, metrics, definitions, and operational reporting across organizations.
• Partner with technical and business teams to understand source systems, reporting needs, and integration priorities.
• Help establish a durable data foundation that supports organizational growth and future acquisitions or integrations.
• Data Governance, Quality, and Reliability
• Establish data governance frameworks, lineage, quality checks, observability, and operational standards.
• Implement monitoring, alerting, validation, and recovery mechanisms for critical data pipelines.
• Improve data reliability, consistency, documentation, discoverability, and trust.
• Define and promote engineering best practices for data ingestion, transformation, testing, deployment, and maintenance.
• Identify and resolve data quality issues in partnership with analytics, technology, and business stakeholders.
• Analytics Enablement
• Partner closely with analytics, product, editorial, marketing, subscriptions, advertising, philanthropy, finance, and operations teams.
• Enable high-quality dashboards and reporting through curated datasets, semantic models, and trusted data sources.
• Support Power BI reporting infrastructure and optimize downstream analytical workflows.
• Translate business needs into scalable data models and analytical solutions.
• Help teams across the organization use data more effectively, consistently, and confidently.

Requirements

• 10+ years of experience in data engineering, analytics engineering, backend engineering, or related data platform roles.
• Strong experience designing, building, and operating modern cloud-based data platforms on AWS.
• Strong experience building and orchestrating ETL and ELT pipelines at scale.
• Experience working with data lakes, data warehouses, lakehouse architectures, or similar cloud-native data ecosystems.
• Strong understanding of data governance, lineage, quality, observability, and reliability concepts.
• Experience supporting BI and analytics platforms, including Microsoft Power BI.
• Ability to design scalable data models and curated datasets that support reporting, analytics, and decision-making.
• Strong SQL skills and experience working with complex operational and analytical data sources.
• Strong communication skills and the ability to work directly with business stakeholders.
• Ability to balance technical rigor with practical execution in a fast-moving environment.
• A collaborative mindset and comfort working across technical, analytical, and non-technical teams.
• Experience building enterprise data lakes or lakehouse architectures.
• Experience with media, publishing, subscription, advertising, audience analytics, or digital consumer product data.
• Experience integrating data from content management systems, subscription platforms, advertising systems, CRM systems, finance systems, or marketing platforms.
• Experience with modern data transformation, orchestration,

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