Lead Data Engineer: End-to-End Data Lake, Databricks & dbt in Newcastle

Lead Data Engineer: End-to-End Data Lake, Databricks & dbt in Newcastle

Newcastle Full-Time 63000 - 77000 $ / year (est.) On-site
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At a Glance

  • Tasks: Lead the design and delivery of data pipelines using Databricks and dbt.
  • Company: Join EPAM Systems, a global leader in tech innovation.
  • Benefits: Enjoy competitive pay, flexible work options, and career growth.
  • Other info: Work in a dynamic team with opportunities for professional development.
  • Why this job: Make a significant impact on enterprise-level data solutions.
  • Qualifications: Experience in data engineering and strong collaboration skills required.

The predicted salary is between 63000 - 77000 $ per year.

EPAM Systems, Inc. in Australia is seeking a Lead Data Engineer to own end-to-end data modeling and pipeline delivery as a major enterprise data lake is re-architected. You will work hands-on with Databricks and dbt, partnering with US stakeholders and collaborating with an India-based engineering team. You thrive with high autonomy, clear documentation, and strong ownership, delivering across requirements, build, testing, UAT, and deployment while maintaining technical docs in Confluence.

Lead Data Engineer: End-to-End Data Lake, Databricks & dbt in Newcastle employer: EPAM Systems, Inc.

At EPAM, we pride ourselves on being a Great Place To Work-Certified employer, offering a supportive environment where your ideas drive our success. As a Client Partner in Sydney, you'll collaborate with top talent and cutting-edge technologies while enjoying transparent career paths and extensive self-development opportunities. Join us to grow your career in a dynamic setting that values your contributions and fosters innovation.

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Contact Details:

EPAM Systems, Inc. Recruitment Team

We think you need these skills to ace Lead Data Engineer: End-to-End Data Lake, Databricks & dbt in Newcastle

Communication Skills
Python
Data Engineering
Problem-Solving Skills
SQL
ETL/ELT Processes
Data Warehousing