Data Transformation Specialist

7 days ago

Melbourne, Victoria, Australia beBeeData Full time $100,000 - $150,000
Job Summary

We are seeking a skilled Data Solutions Engineer to join our team. As a key member of the DNA team, you will be responsible for designing, building, and maintaining end-to-end data stacks that include data ingestion, data warehousing, and data transformation pipelines.

This is an excellent opportunity for a motivated and experienced professional to contribute to high-end innovative technological solutions with clients, develop data and AI-led initiatives for transformation, and play a key role in the execution and delivery of such engagements.

Responsibilities:

  • Deliver high-quality data solutions and maintain an entire data stack including data ingestion, data warehouse, and data transformation pipelines.
  • Build resilient, secure, high-performance infrastructure for ETL/ELT processes across varied data sources using SQL, data lake, and Databricks technologies.
  • Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and deliver data-driven solutions.
  • Design, build, and maintain scalable and reliable data pipelines (ETL/ELT) into data warehouses and data lakes.
  • Define data models, schemas, and architectures ensuring data quality, integrity, performance, and availability.
  • Contribute to deployments and innovations with clients to support data and AI-led transformation initiatives.
  • Provide guidance and mentorship to data engineers and lead projects and initiatives.
Requirements
  • Bachelor's degree in Computer Science, Engineering, Information Systems, or related field.
  • Proficiency in Python, Java, Scala, or R; experience building and optimizing code for data processing.
  • Experience with cloud data warehouse solutions (Snowflake, Redshift, BigQuery, Azure).
  • Experience with data ingestion tools (Fivetran, Stitch, Matillion).
  • Strong scripting skills (Bash) and data pipeline/tools (Airflow, Azkaban).
  • Experience with big data technologies (Hadoop, Spark, Kafka, Cassandra) and cloud services (AWS EMR, Azure HDInsight, Google Cloud Dataproc).
  • Strong data modeling, data warehousing principles, and SQL proficiency.
  • Experience with data visualization tools (Tableau, Power BI).
  • Mentorship capabilities and ability to lead projects; strong problem-solving and communication skills.
  • Experience with CI/CD, automated testing, and performance engineering; familiarity with Git.
  • Knowledge of Connect-Direct, Ctrl-M Scheduler, Elasticsearch (ELK Stack), and Splunk is a plus.

Employment Details:

  • Seniority level: Mid-Senior level
  • Employment type: Full-time
  • Job function: Information Technology
  • Industry: Information Services

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