dunnhumby
Tech / AI / Software
SeniorBigDataEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Big Data Engineer at dunnhumby. Skills: Big Data Engineering, Data Architecture, Data Pipelines, Cloud Platforms, Data Governance. 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.”
Industry & Context.
detect anomalies; automatically reroute or restart processes; maintain data integrity and availability
What They're Looking For.
Must Have
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)., 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 Hadoop/Spark Toolsets., Extensive Experience working with Git and Process Automation, In depth understanding of relational database management systems (RDBMS) and Data Flow Development.
What You'll Do.
Design end-to-end data solutions
and analytics platforms.
Architect scalable and low-latency data pipelines using tools like Apache Kafka
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
and automatically reroute or restart processes to maintain data integrity and availability.
Define and implement data governance
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.
and regulatory requirements are addressed in all data solutions.
Evaluate and recommend improvements to existing data architecture and processes.
How You'll Work.
Team & Collaboration
Partner with business and IT teams to translate business needs into data architecture requirements.
Full Job Description
dunnhumby is the global leader in Customer Data Science, partnering with the world’s most ambitious retailers and brands to put the customer at the heart of every decision. We combine deep insight, advanced technology, and close collaboration to help our clients grow, innovate, and deliver measurable value for their customers. dunnhumby employs nearly 2,500 experts in offices throughout Europe, Asia, Africa, and the Americas working for transformative, iconic brands such as Tesco, Coca-Cola, Nestlé, Unilever and Metro. 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
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