Chief Architect

1 week ago

Sydney, New South Wales, Australia beBeeDataEngineer Full time $150,000 - $200,000
Senior Data Engineer Opportunity

We are seeking a highly skilled professional to join our team in creating innovative technology solutions at the intersection of data, AI, machine learning, and software engineering.

  • The ideal candidate will be responsible for designing and implementing real-time data pipelines and data mesh architectures to enhance client data interactions.

Key Responsibilities:

  • Designing Data Solutions: Implement and enhance data-driven solutions integrating with clients' systems using state-of-the-art tools such as Databricks, Snowflake, Google Cloud, and AWS.
  • Data Pipeline Development: Develop and optimise high-performance, batch and real-time data pipelines employing advanced streaming technologies like Kafka, and Flink.
  • Database and Storage Optimisation: Optimize and manage a broad array of database technologies, from traditional relational databases (e.g., PostgreSQL, MySQL) to modern NoSQL solutions (e.g., MongoDB, Cassandra).
  • Big Data Processing & Analytics: Utilise big data frameworks such as Apache Spark and Apache Flink to address challenges associated with large-scale data processing and analysis.
  • Cloud Data Management: Implement and oversee cloud-specific data services including AWS Redshift, S3, Google BigQuery, and Google Cloud Storage.
  • Security and Compliance: Ensure all data practices comply with security policies and regulations, embedding security by design in the data infrastructure.

Required Skills and Qualifications:

  • Proficiency in SQL and Spark, and familiarity with platforms such as Databricks and Snowflake.
  • Well-versed in various storage technologies including AWS S3, Google Cloud BigQuery, Cassandra, MongoDB, Neo4J, and HDFS.
  • Adept in pipeline orchestration tools like AWS Glue, Apache Airflow, and dbt, as well as streaming technologies like Kafka, AWS Kinesis, Google Cloud Pub/Sub, and Azure Event Hubs.
  • Knowledgeable in data warehousing technologies like BigQuery, Snowflake, and Databricks, proficient in managing various data storage formats including Parquet, Delta, ORC, Avro, and JSON.
  • Experienced in developing and overseeing large-scale data pipelines and data-intensive applications within production environments.
  • Proficient in data modelling, understanding the implications and trade-offs of various methodologies and approaches.
  • Competent in setting up data system infrastructures, favouring infrastructure-as-code practices using tools such as Terraform and Pulumi.
  • Programming languages: Proficient in Python and SQL, with additional experience in programming languages like Java, Scala, GoLang, and Rust considered advantageous.

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