Databricks Data Engineer

1 week ago

Sydney, New South Wales, Australia Mane Consulting Full time
Overview

Databricks Data Engineer | Mid Level role at Mane Consulting. Join to apply for the Databricks Data Engineer | Mid Level role at Mane Consulting.

This range is provided by Mane Consulting. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range: A$700.00/daily - A$800.00/daily

What you'll be doing
  • Working with business and technical stakeholders to understand requirements relating to data and analytics initiatives with a focus on delivering business outcomes
  • Designing, developing, testing, documenting, and maintaining data models, reports, and dashboards that meet business needs and requirements
  • Designing, developing, testing, documenting, and maintaining data pipelines across a range of technologies that extract, load, combine and transform data from a range of internal and external sources
  • Translate business requirements into logical and physical data models, ensuring alignment with reporting and BI needs
  • Understand and implement data governance requirements that support data and analytics solutions including security, data quality, data classification, trustworthiness, and re-usability
  • Design and implement star and snowflake schemas to support scalable, performant analytics across business domains
  • Collaborating with technical and non-technical stakeholders through a range of forums including cross-functional delivery teams, data and analytics practice group, and the data and analytics platform team
Qualifications
  • Extensive expertise in data engineering and data analysis
  • Proficient in T-SQL, SQL Server, Databricks, PySpark, Power BI, and other related data tools and platforms
  • Experience with Lambda and Kappa architecture stacks
  • Hands-on experience building Data Streaming solutions using technologies like Apache Kafka, Azure Event Hub, Confluent, and Apache Flink
  • Skilled in constructing and optimizing data pipelines, data models, reports, and dashboards
  • Experience with Azure data services including Azure Data Factory, Azure Databricks, Delta Lake, and Azure Synapse Analytics
  • Experience in star/snowflake schema design and understanding of slowly changing dimensions (SCD Types 1, 2, etc.)
  • Ability to translate business logic into fact/dimension tables; proficient in handling large and complex datasets
  • Ability to mentor engineers, guide technical decisions, and contribute to overall strategy
Seniority level
  • Mid-Senior level
Employment type
  • Full-time
Job function
  • Information Technology
Industries
  • Information Services

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