Data & Insights Engineer, Customer Solutions
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Job description
About Daltix
Daltix helps leading FMCG and retail companies make better decisions using reliable, accessible and carefully curated product data.
Every day, we collect, standardize and deliver large-scale data on prices, promotions, products and assortments. Our customers—including companies such as Colruyt Group, YouGov and Danone—use this information to understand their markets, monitor competitors and identify commercial opportunities.
Data quality is central to what we do. We remove the complexity of collecting and preparing retail data so our customers can focus on using it.
About the role
We are hiring a Data & Insights Engineer – Customer Solutions for a hands-on, customer-facing role bridging data engineering and analytics. You will build data pipelines and models, analyze large-scale retail datasets, and work directly with customers to turn business needs into practical technical solutions.
Collaborating with our engineering, data science, and product teams, this role is ideal for someone who excels at both solving technical problems and communicating findings to non-technical stakeholders.
Your time will typically be divided between (indicative percentages—may vary by customer project):
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50% Data Engineering: Building and maintaining pipelines, models and customer datasets
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25% Analysis & Insight Delivery: Exploring data and producing reports, dashboards and recommendations
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20% Product & Commercial Support: Identifying reusable solutions and contributing to project scoping
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5% Customer Collaboration: Participate in workshops, defining requirements and supporting customers
What You’ll Do
Data Engineering & Reliability
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Pipelines & Models: Design, build, and maintain SQL/Python ETL/ELT pipelines, data models, and customer-facing datasets.
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Retail Data: Process large-scale product, price, and promotion data.
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Quality & Ops: Ensure data accuracy, monitor pipelines/dashboards, resolve failures, and improve system scalability.
Analytics & Insights
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Solutions: Create reports, dashboards, and analytical solutions using Daltix tools.
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Communication: Present clear insights to both technical and business audiences.
Customer Engagement
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Requirements: Run customer workshops, translate business needs into technical deliverables, and iterate on feedback.
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Support: Drive product adoption, assist users, and resolve data/reporting inquiries.
Tech Tools(Our tech stack evolves—you are not expected to know every tool before joining)
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Hardware & OS: MacBook or Framework running Linux
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Data & Storage: SQL, Snowflake, PostgreSQL
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Code: Python, uv, Pandas
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Orchestration & Infra: Apache Airflow, Docker, Kubernetes
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Internal Tools & Ops: Retool, Git, Jira
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Collaboration & AI: Google Workspace, Slack, modern AI/LLM tools (e.g., Claude)
How we work
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Team & Structure: Join a 4-person team reporting to the Head of Product Delivery, collaborating closely with Data/Platform Engineering, Data Science, and Product Delivery.
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Autonomy & Support: Take ownership of work backed by pairing, code reviews, mentoring, and clear documentation.
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Slack Availability: Active on Slack UTC 08:30–15:00 (includes a flexible 1-hour lunch break).
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On-Call & Monitoring: Monitor customer deliverables on a rotational basis during normal working hours only (no out-of-hours on-call).
Job requirements
What We’re Looking For
Strong fundamentals, practical problem-solving skills, and a desire to learn matter more than knowing every tool in our stack.
Requirements
Core Tech: Strong SQL (relational/analytical DBs) and practical Python (e.g., Pandas).
Data Engineering: solid understanding of ETL/ELT, data warehousing, data modeling, and handling large datasets.
Workflows & Mindset: Git/collaborative workflows, strong analytical problem-solving, and ability to turn business questions into technical deliverables.
Communication & Education: Professional English, confidence with customers/non-technical stakeholders, and a relevant degree (e.g., CS, Business Engineering, Applied Economics) or equivalent experience.
Domain Interest: Eagerness to learn FMCG, retail, and pricing analytics.
Location & Travel: Remote (Europe) or Lisbon-based, requiring ~4 short trips per year (1 to Benelux clients, 3 to Lisbon engineering team) with travel and accommodation expenses fully covered by Daltix.
Nice to have (but not a requirement)
Stack & Tools: Snowflake, PostgreSQL, Airflow, AWS, Docker, Kubernetes, BI tools (Power BI, Tableau, Retool), and notebook environments (Jupyter, Marimo).
Specialized Tech: Data matching, entity resolution, and AI coding/analysis tools.
Domain & Delivery: FMCG/retail/pricing experience, customer-facing consulting, or project delivery.
Languages: Dutch or German.
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