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Leading Data Engineer

3 weeks ago


Sydney, New South Wales, Australia beBeeDataEngineer Full time $120,000 - $150,000
Job Description

Key Responsibilities:

  • Drive the execution of data engineering initiatives, collaborating with cross-functional teams to deliver high-quality results.
  • Provide technical leadership in the data space, identifying risks and solutions, and coordinating with engineers to ensure successful execution.
  • Lead technical solution design and troubleshooting, ensuring the team builds scalable and maintainable systems.
Technical Requirements

Key Skills and Qualifications:

  • Ensure adherence to data privacy, security, observability, and governance standards.
  • Collaborate with architects and senior engineers to design resilient, high-performance data solutions.
  • Build scalable data pipelines to ingest, process, and expose data using technologies like Snowflake, AWS Redshift, Kinesis, Lambda, Dynamo DB, S3, Glue, Apache Storm, and others.
  • Develop batch and streaming data solutions using Apache Kafka, Apache Spark, Airflow, and Delta Lake for real-time and scheduled data processing.
  • Design and implement event-driven data architectures with streaming frameworks such as Kafka Streams and Kinesis Data Firehose.
  • Implement Data Quality, Data Lineage, and Observability frameworks Build CI/CD pipelines using tools such as Git Hub Actions, Terraform, Collaborate with Site Reliability Engineers to ensure stability and uptime of production pipelines and services.
  • Continuously identify opportunities for performance improvement, cost optimisation, and process efficiency.
  • Work with Data Scientists to ensure high-quality data for Machine Learning models and integrate them into production-ready pipelines.
About You

Requirements:

  • Undergraduate degree focused on Computer Science, Engineering, Data Science or a related discipline.
  • 5+ years of hands-on experience in data profiling, source-to-target mapping, ETL development, SQL optimisation, testing, and implementation.
  • Proven experience delivering large-scale data ingestion, transformation, and processing using AWS technologies such as Kinesis, Athena, Redshift, Dynamo DB, Lambda, and S3.
  • Proficient with modern data platforms and tools including Snowflake, Databricks and Apache Storm.
  • Strong experience working with relational databases (SQL) as well as No SQL databases, particularly Mongo DB.
  • Proven ability to translate complex business requirements into technical solutions through effective cross-functional collaboration, strong communication skills, and adaptable problem-solving approach.
  • Exposure to CI/CD tools and practices, including Ansible, Cloud Formation, Jenkins, and related automation technologies.
  • Experience developing and deploying solutions on cloud platforms such as AWS, GCP, or Azure.