**Please submit your resume in English only**

Harvest Group is an integrated commerce agency that helps high-growth consumer brands win in today's complex retail landscape. Since 2006, we've partnered with some of the world's most recognized brands to navigate the intersection of in-store and digital commerce, retail media, and social platforms across leading retailers including Walmart, Sam's Club, Target, Amazon, Costco, and Kroger. 

What sets Harvest Group apart is our connected approach. By aligning strategy, execution, and insights across every stage of the retail journey, and powering that work through our proprietary technology platform, we help brands create sustainable growth in an increasingly dynamic marketplace. 

But our success starts with our people. 

At Harvest Group, our culture and values shape how we work, serve our clients, and support one another. We believe in building meaningful relationships, pursuing excellence with humility, and creating an environment where talented individuals can do their best work while continuing to grow professionally and personally. 

Our Values 

• Integrity – Doing what is right in all things 

• Relationship – Pursuing depth, trust, and collaboration 

• Service – Laboring for others with humility and care 

• Excellence – Delivering extraordinary performance and results with humility 

• Journey – Embracing our past and planning for our future with faith 

Harvest Group Tunisia is the third branch of the Harvest Group company, which opened in 2016. Its main responsibilities are: 

• Data reporting and insights: standardized and optimized reports and performance trackers for U.S. teams and clients 

• Analytical storytelling: leveraging data to tell a compelling story 

• Software development: supporting the dynamic needs of our team 

• Tool creation: building easy-to-use solutions to complex data problems 

• Data operations and cloud data management: building and maintaining data pipelines from source systems to cloud data storage, and retrieving data from a wide variety of sources 

About the Role 

The Senior Data Engineer is a technical leader responsible for the architecture, quality, and reliability of the data pipelines and models within an assigned data product team, supporting retail partners including Walmart, Sam's Club, Target, Amazon, Costco, and Kroger. This role owns major subsystems of the data platform, designs solutions that span multiple data domains, and sets the engineering standards the team follows. The Senior Data Engineer applies deep expertise in data architecture and data operations alongside the ability to mentor others, influence the roadmap, and drive continuous improvement. This role serves as the primary technical authority on the team, partnering with product managers, analysts, and platform engineers to deliver data products that meet Harvest Group's standards for quality, performance, and reliability. 

What You'll Do 

• Design and own the data architecture for complex, multi-domain data products. 

• Review and evolve warehouse structures, including data models, schemas, and naming and metadata conventions, to ensure clear business semantics and consistent definitions. 

• Architect and maintain semantic and metadata layers that enable governed, scalable access to data for business users and analytics tools. 

• Partner with business stakeholders to understand key questions, decisions, and workflows, then translate those needs into durable data structures and models. 

• Lead technical design reviews and backlog refinement within Agile/Scrum delivery, establishing architecture patterns the team adopts. 

• Set and enforce engineering quality standards: testing strategies, code review expectations, and documentation norms. 

• Optimize cloud warehouse performance: query tuning, warehouse sizing, materialization strategies, and cost management. 

• Build advanced transformation patterns: custom macros, reusable packages, and complex incremental and snapshot strategies. 

• Design orchestration architectures for reliability, observability, and SLA compliance. 

• Stand up proofs of concept to evaluate new data patterns or approaches, then harden successful designs into production-ready solutions. 

• Ensure data quality, performance, security, and governance practices are embedded in the solutions the team ships. 

• Identify systemic data quality issues and implement preventive solutions. 

• Mentor Data Engineer I and II team members, conducting code reviews and leading technical discussions. 

• Partner with product managers to translate business strategy into a technical data engineering roadmap. 

• Collaborate with platform engineering on shared infrastructure and tooling, and contribute to cross-team engineering standards and architecture decision records. 

What We're Looking For 

Required 

• 5+ years of experience in data engineering, data architecture, or analytics engineering. 

• Expert SQL skills, including advanced query optimization for cloud data warehouses. 

• Strong data modeling skills for analytical use cases (dimensional modeling, slowly changing dimensions, data vault). 

• Deep production experience with a SQL-based transformation framework (dbt preferred). 

• Experience designing and operating data pipelines at scale with an orchestration platform (Airflow preferred). 

• Experience working across the full data lifecycle, from raw ingestion to analysis-ready datasets. 

• Advanced version control and CI/CD practices (Git), including branching strategy and release standards. 

• Advanced Python for production data engineering workloads. 

• Track record of mentoring engineers and raising team engineering quality. 

• Proven ability to take solutions from concept through production with attention to reliability, scalability, and maintainability. 

• Ability to explain complex technical concepts to non-technical audiences. 

• Excellent written and verbal communication skills in English. 

• Ability to collaborate effectively with U.S.-based teams and clients across time zones. 

• Ownership mindset with a proactive approach to problem solving and continuous improvement. 

Nice to Have. 

• Experience building or managing semantic layers (dbt Semantic Layer, Looker semantic models, AtScale, Cube, or similar). 

• Experience building and maintaining shared transformation packages or frameworks. 

• Familiarity with infrastructure-as-code for data platform resources (Terraform preferred). 

• Experience with data observability and monitoring platforms. 

• Background in data governance, metadata management, and access controls. 

• Deep expertise with CPG or retail data across multiple retailers (Kroger / 84.51, Walmart / Luminate, Nielsen, Circana). 

• Experience building data structures and pipelines that support AI and LLM applications, including retrieval over both structured and unstructured data. 

We encourage all interested candidates to apply. 

What We're Looking For 

Required 

• 5+ years of experience in data engineering, data architecture, or analytics engineering. 

• Expert SQL skills, including advanced query optimization for cloud data warehouses. 

• Strong data modeling skills for analytical use cases (dimensional modeling, slowly changing dimensions, data vault). 

• Deep production experience with a SQL-based transformation framework (dbt preferred). 

• Experience designing and operating data pipelines at scale with an orchestration platform (Airflow preferred). 

• Experience working across the full data lifecycle, from raw ingestion to analysis-ready datasets. 

• Advanced version control and CI/CD practices (Git), including branching strategy and release standards. 

• Advanced Python for production data engineering workloads. 

• Track record of mentoring engineers and raising team engineering quality. 

• Proven ability to take solutions from concept through production with attention to reliability, scalability, and maintainability. 

• Ability to explain complex technical concepts to non-technical audiences. 

• Excellent written and verbal communication skills in English. 

• Ability to collaborate effectively with U.S.-based teams and clients across time zones. 

• Ownership mindset with a proactive approach to problem solving and continuous improvement. 

Nice to Have. 

• Experience building or managing semantic layers (dbt Semantic Layer, Looker semantic models, AtScale, Cube, or similar). 

• Experience building and maintaining shared transformation packages or frameworks. 

• Familiarity with infrastructure-as-code for data platform resources (Terraform preferred). 

• Experience with data observability and monitoring platforms. 

• Background in data governance, metadata management, and access controls. 

• Deep expertise with CPG or retail data across multiple retailers (Kroger / 84.51, Walmart / Luminate, Nielsen, Circana). 

• Experience building data structures and pipelines that support AI and LLM applications, including retrieval over both structured and unstructured data. 

We encourage all interested candidates to apply.