Highly Skilled Data Architect

1 week ago

Sydney, New South Wales, Australia beBeeDataEngineer Full time $145,000 - $173,000
Senior Data Engineer

We are seeking a seasoned data engineer to spearhead the design and implementation of large-scale data infrastructure. This individual will be responsible for architecting, building, and maintaining scalable data pipelines, as well as collaborating with cross-functional teams to drive business outcomes.

The ideal candidate will possess a strong background in cloud data platforms, programming languages such as Python or Java, and experience working with relational and NoSQL databases. Additionally, they should have a solid understanding of real-time processing technologies, workflow orchestration tools, and data transformation frameworks.

Key Responsibilities:
  • Data Pipeline Design and Development: Design, build, and optimize enterprise-scale ETL/ELT pipelines to support analytics, business intelligence, and machine learning initiatives.
  • Real-Time Streaming Solutions: Develop real-time streaming solutions for workforce analytics and automated decision-making.
  • AI Automation Foundation: Build the data foundation for AI automation initiatives.
Requirements:
  • Technical Expertise: 5+ years of experience building production data pipelines and ETL/ELT processes. Strong experience with cloud data platforms, programming languages, and databases.
  • Cloud Platforms: Experience with AWS (S3, Lambda, Glue, EMR) and modern data warehousing (Snowflake or Redshift).
  • Programming Languages: Proficiency in Python or Java for data processing applications.
  • Databases: Advanced SQL skills and experience with both relational and NoSQL databases.
  • Real-Time Processing: Experience with streaming technologies like Apache Kafka, Apache Flink, or AWS Kinesis.
  • Workflow Orchestration: Experience with workflow orchestration tools (Apache Airflow, Prefect, or similar).
  • Data Transformation: Experience with data transformation tools (DBT, FiveTran, AWS Glue).
  • Containerization: Knowledge of containerization technologies (Docker, Kubernetes).
  • Data Security and Compliance: Understanding of data security, privacy, and compliance frameworks.
  • Education: Bachelor's or master's degree in Computer Science, Engineering, Information Systems, or a related field.

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