Senior Data Engineer

🔥 12 hours ago

🇵🇹 Portugal – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Valtech

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

Founded 1997

💼 Consulting

📣 Marketing

☁️ SaaS

Consulting • Marketing • SaaS

Valtech is a global digital agency focusing on experience innovation. They strive to transform businesses through a combination of technology, marketing, and data strategies. Valtech helps companies elevate their digital presence and drive commerce strategies, enhance enterprise digital transformations, and unlock marketing and performance potential. They also utilize data and AI to help organizations harness the power of information. With offices around the world, Valtech partners with businesses to shape their digital futures, offering a range of services and insights designed to enhance customer experiences.

📋 Description

• Design, build, and optimize modern cloud-based data platforms powering analytics, AI, and data products • Develop reliable batch, streaming, and near-real-time pipelines for structured and unstructured data • Build ingestion, transformation, curation, and data-serving workflows • Implement lakehouse architectures and medallion layering in Databricks or Fabric • Deliver curated datasets for analytics, machine learning, causal modeling, optimization, GenAI, RAG, and agent-based systems • Use MLflow, Unity Catalog, Azure ML, and equivalent platform tooling to support production-grade AI systems • Design data models and orchestrate workflows using Airflow, dbt, Databricks Workflows, Azure Data Factory, or equivalents • Apply data governance, lineage, quality, access control, and observability practices • Monitor data freshness, pipeline reliability, SLA adherence, performance, scalability, and cost efficiency • Enable APIs, feature inputs, and analytical endpoints for downstream ML and AI systems • Discover and refine business requirements through stakeholder engagement and analysis • Collaborate with data scientists, ML engineers, analysts, platform teams, and business stakeholders • Support adoption of data products and contribute to data and AI best practices

🎯 Requirements

• Strong hands-on experience with Apache Spark and Delta Lake • Strong programming skills in Python and SQL • Proven experience building batch and streaming data pipelines and production-grade data platforms • Solid understanding of data modeling, data quality, and governance principles • Strong, demonstrable hands-on experience with either AWS data services and the Databricks Lakehouse Platform, or Microsoft Azure/Fabric and related tooling • Experience with lakehouse architectures and distributed data systems • Strong understanding of scalability, reliability, and performance considerations in data pipelines • Naturally curious, with strong problem-solving skills • Collaborative approach to working in cross-functional teams • Experience in Agile or consulting environments is beneficial • Familiarity with Snowflake or GCP is a plus but not required • Deep expertise in both AWS and Azure/Fabric, GenAI and AI data systems, CI/CD for data pipelines, and infrastructure-as-code tools are nice to have but not required • Additional exposure to Kafka, Spark optimization, advanced analytics and ML workloads, or large-scale analytics platforms is valuable

🏖️ Benefits

• Flexibility, with remote and hybrid work options (country-dependent) • Career advancement, with international mobility and professional development programs • Learning and development, with access to cutting-edge tools, training and industry experts • Competitive compensation package