Data Solutions Architect

3 days ago

Melbourne, Victoria, Australia beBeeData Full time $150,000 - $170,000

As a Data Solutions Architect, you will play a key role in designing and implementing data engineering solutions that drive business value.

Job Description:

We are seeking an experienced professional with expertise in data warehousing, ELT/ETL, and data extraction and manipulation in a data lake/data warehouse environment. Your primary responsibility will be to design, develop, and maintain scalable and high-performance data solutions that meet the needs of our organization.

Key Responsibilities:
  • Data Modeling and Analysis: Proven experience in data modeling, analysis, and profiling is crucial for success in this role.
  • Diverse Data Domains: Experience of working in diverse data domains is essential.
  • Performance Optimization: Continuous improvement and performance optimization practice ensuring high levels of performance, availability, and integrity.
  • Consulting and Mentoring: Proven consulting and mentoring experience is required.
  • Agile Environment: Experience in working within an Agile environment.
Technical Requirements:
  • Data Engineering Practices: In-depth understanding of data engineering practices and big data technologies.
  • SQL and Big Data Technologies: Hands on in SQL and its Big Data variants (Hive-QL, Snowflake ANSI, Redshift SQL).
  • Programming Languages: Python and Spark and one or more of its API (PySpark, Spark SQL, Scala), Bash/Shell scripting.
  • Source Code Control: Experience with Source code control - GitHub, VSTS etc.
  • Big Data Technologies: Knowledge and exposure to Big Data technologies Hadoop stack such as HDFS, Hive, Impala, Spark etc, and cloud Big Data warehouses - RedShift, Snowflake, Databricks etc.
  • UNIX Command-Line Tools: Experience with UNIX command-line tools.
  • AWS Technologies: Exposure to AWS technologies including EMR, Glue, Athena, Data Pipeline, Lambda, etc.
Desirable Skills:
  • Cloud Computing: Cloud computing knowledge.
  • Containerization: Containerization using Docker.
  • Monitoring and Logging: Monitoring and logging tools like Prometheus, Grafana, ELK.

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