SGS Principal Data Engineer \\\| SmartRecruiters Google Chrome Microsoft Edge Apple Safari Mozilla Firefox . Principal Data Engineer Full-time Company Description We are SGS the world's leading testing, inspection and certification company. We are recognized as the global benchmark for sustainability, quality and integrity. Today, that mission is driven by data. With 99,500 employees across 2,500 locations, we generate a unique and massive dataset on global trade, product quality, and sustainability. We are now launching a new Hub in Madrid to turn that data into intelligent products and services. This is your opportunity to build the engine that will power our next generation of digital solutions. Job Description This isn't a standard ETL role. We're looking for a data systems pioneer to build our entire data ecosystem from scratch with the executive backing and autonomy to make it happen. The Vision: Imagine a central data platform that ingests real-time IoT data from industrial inspections to predict equipment failures, or unifies decades of lab results to optimise entire supply chains.You'll buildthisanalytics engineand the high-performance, real-time data backends for our most critical products. If you're excited by the challenge of turning messy, complex,real-worlddata into fast, reliable products, this is your role. As a Principal Data Engineer, you will own the flow of data across our organization. Your dual mission is to: 1) Engineer a central, world-class analytics engine that provides clean, trustworthy data for AI and business intelligence. 2) Architect and build the data-intensive backends for our flagship products, selecting the right tools to ensure low-latency and high-reliability. What You'll Build and Own Architect Product Data Layers: Design the data models and select the optimal persistence technologies (e.g., PostgreSQL, NoSQL, Time-Series DBs) for new, high-throughput digital products. Build the Core Analytics Engine: Engineer our core data platform using modern tools like dbt, Spark, and cloud warehouses (Snowflake, BigQuery, or Databricks) to create a single source of truth. Develop High-Performance Pipelines: Build and operate robust, observable data pipelines for both massive batch processing and low-latency, real-time streams (e.g., using Kafka, Flink). Harvest & Generalize Data Patterns: Identify common data challenges and solutions, packaging them into reusable pipelines, modules, and best practices for other teams to leverage. Champion Data Quality: Implement and promote a strong data quality culture using modern frameworks (e.g., Great Expectations) to ensure our data is always trustworthy. Grow the Foundation: As the first Principal on the team, you will play a key role in shaping our technical culture and mentoring future hires as we build out the data engineering function. Qualifications Data Platforms & Warehousing: Deep expertise in modern cloud data platforms like Snowflake, BigQuery, or Databricks (Delta Lake). Data Processing & Transformation: Expert-level proficiency with Apache Spark (PySpark/Scala) and modern data transformation tools, especially dbt. Application Data Architecture: Proven experience designing data models for transactional systems. Hands-on experience with PostgreSQL is essential; experience with NoSQL or Time-Series DBs is a strong plus. Streaming & Orchestration: Hands-on experience with workflow orchestration (Airflow, Dagster) and real-time streaming technologies (Kafka, Flink). Programming & SQL: Expert-level SQL and strong programming skills in Python or Scala for data engineering. Who You Are You are a pragmatic data systems builder with extensive (8+ years) of experience. You have a proven track record of turning complex, messy data into reliable, high-performance products and platforms. You thrive on greenfield challenges and have architected major data systems from the ground up. You are a pragmatist who can balance the needs of large-scale analytics with the low-latency demands of user-facing applications. You are obsessed with data quality and building systems that are both powerful and trustworthy. Additional Information What We Offer: Top-of-Market Compensation: A highly competitive salary and bonus package for Madrid, designed to attract and retain premier talent for this strategic role. Greenfield Ownership & Autonomy: This is not an optimization role. You have a mandate to build from scratch with the freedom to choose the right tools for the job, backed by C-level sponsorship. Foundational Impact: You will be the first Principal Data Engineer in our new Digital Hub, shaping the technology, culture, and future of data at a global leader. A Compelling Problem Space: Work on unique, tangible data challenges that have a real-world impact on global safety, sustainability, and supply chains. A Clear Growth Path: This role offers a direct path to technical leadership and the opportunity to build and mentor a team around your architectural vision. Videos To Watch Job Location Google Maps requires functional cookies to be enabled I'm interested I'm interested I'm interested Refer a friend Posted by Ismael Guindo share this job Share on LinkedIn Share on Facebook Share on Twitter Share via email Share on Xing Share on WeChat Other jobs at SGS Senior Civil Engineer Tucson, AZ AI Engineer Madrid, Spain Data Engineer Madrid, Spain Show all jobs Share to WeChat × Copy the link and open WeChat to share. Copy to clipboard Open WeChat Share to WeChat × Use Scan QR Code in WeChat and click ··· to share. × Continue Principal Data Engineer C. Trespaderne, 29, Barajas, 28042 Madrid, Spain Full-time I'm interested I'm interested

The role requires deep expertise in modern cloud data platforms such as Snowflake, BigQuery, or Databricks (Delta Lake). Expert-level proficiency with Apache Spark (PySpark/Scala) and modern data transformation tools, particularly dbt, is essential. Proven experience designing data models for transactional systems and hands-on experience with PostgreSQL are necessary. Experience with workflow orchestration tools like Airflow or Dagster and real-time streaming technologies such as Kafka or Flink is also required. Expert-level SQL and strong programming skills in Python or Scala for data engineering are fundamental. The ideal candidate has extensive experience, specifically 8+ years, as a pragmatic data systems builder with a track record of turning complex data into reliable products and platforms.