Design scalable ETL/ELT pipelines using Databricks and DBT

Implement data models that facilitate cost analytics and reporting

Work with Cloud Operations and Finance teams to uncover cost reduction possibilities

Automate data ingestion from diverse sources such as cloud billing APIs and usage logs

Maintain data quality, governance, and compliance for all datasets

Optimize data processing speed and storage expenses in cloud platforms

Support the offshore delivery model and coordinate with global stakeholders

Minimum 3 years in Data Engineering or a similar discipline

Background in Databricks (Spark, Delta Lake) and DBT for data transformation

Proficiency in SQL and PySpark for data processing

Skills in software engineering with Python, including object-oriented programming and design patterns

Familiarity with cloud platforms such as Azure, AWS or GCP and their cost management tools

Understanding of data warehousing concepts and the modern data stack

Experience with CI/CD pipelines and version control systems like Git

Strong communication skills for collaboration in a distributed team

Knowledge of FinOps principles and cloud cost optimization strategies

Familiarity with Databricks systems table for extracting Databricks-related insights

Proficiency in Power BI, Tableau or other visualization tools

Understanding of orchestration tools such as Databricks Workflows, Airflow or Prefect

Competency in observability practices and tools including OpenTelemetry, Prometheus and Grafana