Senior Big Data Engineer

About dunnhumby dunnhumby is the global leader in Customer Data Science, helping the world's most ambitious retailers and brands put the customer at the heart of every decision. With nearly 3,000 experts across Europe, Asia, Africa and the Americas, we partner with iconic businesses like Tesco, Coca-Cola, Meijer, Procter & Gamble and Metro to turn data into growth, innovation and measurable value for their customers. Target Our Target team is at the heart of one of dunnhumby’s most exciting partnerships — bringing customer data science to one of America’s most iconic retailers. Working with Target’s over 100 million Target Circle members, we turn unrivalled guest data into growth, helping shape ranges, pricing, promotions and the personalised experiences that keep Target guests coming back About the Role We’re looking for a Sr Big Data Engineer who expects more from their career. It’s chance to extend and improve dunnhumby’s Data Engineering Team. It’s an opportunity to work with a market-leading business to explore new opportunities for us and influence global retailers. Key Responsibilities Design end-to-end data solutions, including data lakes, data warehouses, ETL/ELT pipelines, APIs, and analytics platforms. Architect scalable and low-latency data pipelines using tools like Apache Kafka, Flink, or Spark Streaming to handle high-velocity data streams. Design /Orchestrate end-to-end automation using orchestration frameworks such as Apache Airflow to manage complex workflows and dependencies. Design intelligent systems that can detect anomalies, trigger alerts, and automatically reroute or restart processes to maintain data integrity and availability. Define and implement data governance, metadata management, and data quality standards. Lead architectural reviews and technical design sessions to guide solution development. Partner with business and IT teams to translate business needs into data architecture requirements. Ensure security, compliance, and regulatory requirements are addressed in all data solutions. Evaluate and recommend improvements to existing data architecture and processes. Technical Expertise Bachelors or masters degree in computer science, Information Systems, Data Science, or related field. Extensive experience with high level programming languages - Python, Java or Scala 5+ years of experience in data architecture, data engineering, or a related field. Proficient in data pipeline tools such as Apache Spark, Kafka, Airflow, or similar. Experience with data governance frameworks and tools (e.g., Collibra, Alation, OpenMetadata). Strong knowledge of cloud platforms (Azure or Google Cloud), especially with cloud-native data services. Experience working in Agile or DevOps environments. Experience with modern data stack tools (e.g., dbt, Snowflake, Databricks). Experience with Hive, Oozie, Airflow, HBase, MapReduce, Spark along with working knowledge of…