Data Engineering Manager

The Data Engineering Manager is responsible for leading the design, development, and maintenance of the company’s data infrastructure and analytics platforms. This role ensures that high-quality, reliable, and scalable data systems power the organization’s decision-making, reporting, and advanced analytics initiatives. 

 

Working closely with the Analytics Manager and cross-functional stakeholders across marketing, SEO, product, engineering, and finance, the Data Engineering Manager translates business needs into robust data solutions that enable accurate performance measurement, affiliate tracking, and strategic insights. In addition, this role will ensure that our data infrastructure not only supports reporting and analytics, but also powers our products and platforms in near real time - bridging our data ecosystem with systems such as Sub Affiliation, our websites, and AI-driven capabilities. 

 

The ideal candidate will bring deep technical expertise in cloud data engineering (AWS and/or Azure), experience managing data pipelines and platforms at scale, and a strong understanding of the affiliate and digital marketing ecosystem. 

YOUR CHALLENGE:

• Design and manage scalable data architecture across multiple cloud environments (AWS, Azure, and Microsoft Fabric), ensuring security, reliability, and cost efficiency. 

• Lead the development and optimization of ETL/ELT pipelines and data models (e.g., star schema, data vault, or lakehouse) supporting business intelligence and analytics needs. 

• Collaborate with the Analytics Manager to define and support advanced analytics requirements, including predictive modeling, attribution analysis, and marketing performance optimization. 

• Oversee the integration of affiliate, marketing, and SEO data sources, enabling accurate revenue and performance tracking across brands, partners, and channels. 

• Implement and maintain
  data governance, lineage tracking, and quality frameworks, ensuring compliance with GDPR, CCPA, and internal data standards. 

• Drive automation and continuous integration in data workflows using GitHub, CI/CD pipelines, and infrastructure-as-code (Terraform, CloudFormation). 

• Monitor and optimize
  data platform performance, implementing observability practices to ensure high availability and reliability. 

• Enable near real-time data streaming and APIs that connect the data warehouse with operational systems, supporting Sub Affiliation, website personalization, and AI-driven features. 

• Bridge analytical and operational data flows, ensuring the data platform powers both business intelligence and production use cases across products and core systems. 

• Partner with internal teams to define and enforce data SLAs, ensuring critical data is timely, accurate, and actionable. 

• Promote the adoption of Power BI and Looker for data visualization, self-service analytics, and executive reporting. 

• Contribute to strategic planning and data roadmap development, ensuring alignment between technical investments and business priorities. 

Leadership and Team Management Responsibilities 

• Lead, mentor, and grow a team of data engineers and platform specialists, fostering a culture of collaboration, ownership, and technical excellence. 

• Partner with the Analytics Manager to ensure the data engineering and analytics functions work cohesively to deliver integrated, high-value insights. 

• Drive a learning culture by encouraging experimentation, automation, and continuous improvement in data workflows. 

• Collaborate with senior stakeholders to translate data initiatives into clear business outcomes and ensure alignment across departments. 

• Define performance goals, manage resource allocation, and oversee professional development within the team. 

• Champion best practices in data architecture, software engineering, and agile delivery, ensuring scalability and long-term platform sustainability. 

• Represent the data engineering function in executive and cross-functional discussions, providing thought leadership on data strategy and technology direction.

 

TO DO IT, YOU WILL NEED:

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or related field. 

• 6-12+ years of experience in data engineering, data architecture, or analytics engineering roles. 

• 3-5+ years of leadership or management experience in a data-focused team environment. 

• Proven experience in building and managing data infrastructure and pipelines at scale in AWS and/or Azure environments. 

• Background in affiliate marketing, SEO-driven media, or performance marketing is a strong plus. 

• Proficiency in Python and SQL for data processing, transformation, and optimization. 

• Expertise in ETL/ELT orchestration and data modeling using tools such as Airflow, dbt, or Microsoft Fabric Data Pipelines. 

• Experience with AWS (Redshift, Glue, S3, Athena) and Azure (Synapse Analytics, Data Factory, ADLS, Microsoft Fabric). 

• Experience with real-time or event-driven data technologies, such as Kafka, Kinesis, or Azure Event Hubs, to support near real-time data processing and product integrations. 

• Familiarity with API-based data delivery and model-serving patterns (e.g., REST, GraphQL, or microservices) for powering applications and machine learning workflows. 

• Knowledge of infrastructure-as-code (Terraform, CloudFormation) and CI/CD pipelines via GitHub. 

• Strong understanding of data governance, observability, and quality frameworks. 

• Experience with Power BI and Looker for BI and visualization. 

• Familiarity with Jira and Confluence for project management and documentation. 

• An understanding of affiliate tracking systems (Income Access, CellExpert, NetRefer) and digital marketing data sources (GA4, Ahrefs, Semrush) is a plus. 

• Exceptional communication and stakeholder management skills. 

• Strong analytical mindset with the ability to balance strategic thinking and technical execution. 

• Demonstrated ability to lead and inspire teams in a fast-paced, data-driven environment. 

• Collaborative, proactive, and adaptable to changing priorities.