The SpringCube team curated the following job opportunity to help you in your job search. Explore the position below to find your next career move.
Company Overview
A global technology consultancy specializing in designing, developing, and scaling digital and sustainable products and services.
Senior Azure Data Engineer
YOUR RESPONSIBILITIES:
- Design, implement, and maintain robust and scalable data pipelines to ingest, transform, and process structured and unstructured data from various sources.
- Build and manage data warehouses and data lakes, implementing efficient data storage and retrieval mechanisms. Design data models that support business requirements and analytics use cases.
- Leverage cloud platforms (e.g., AWS, Azure, GCP) to design and deploy scalable data infrastructure, optimizing for performance, cost-effectiveness, and reliability.
- Implement data quality checks, validation processes, and data governance frameworks to ensure data accuracy, integrity, and compliance with security standards.
- Continuously monitor and optimize data pipelines and infrastructure to improve processing speed, reduce latency, and enhance overall system performance.
- Work collaboratively with data scientists, analysts, and other stakeholders to understand their data needs, provide technical expertise, and deliver solutions that meet business objectives.
- Support business users by implementing data presentation layer including data visualisation using tools like Tableau, PowerBI etc.
- Stay up-to-date with emerging technologies and industry trends in the big data and data engineering space, evaluating and implementing innovative solutions to improve data processing capabilities.
- Support the definition and optimization of underlying data infrastructure
WHO YOU ARE:
- You hold a Bachelor’s, Master’s, or Ph.D. degree in IT, Information Management, and/or Computer Science with at least 6 years of experience.
- Good knowledge of the big data technology landscape and concepts related to distributed storage/computing
- Experience with big data frameworks (e.g. Hadoop, Spark) and distributions (Cloudera, Hortonworks, MapR)
- Experience with batch & ETL jobs to ingest and process data from multiple data sources
- Experience with NoSQL databases (e.g. Cassandra, MongoDB, Neo4J, ElasticSearch)
- Experience with querying tools (e.g Hive, Spark SQL, Impala)
- Experience with PowerBI
- Experience or willingness to go in real-time stream processing, using solutions such as Kafka, AWS Kinesis, Flume, and/or Spark Streaming
- Experience or willingness to learn about DevOps and DataOps principles (e.g Infrastructure as Code, automating different parts of the data pipeline)
- High-level understanding of Data Science concepts and methodologies (how models are built, trained, and deployed)
- You are passionate about technology and continuous learning comes naturally to you
Disclaimer
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