About:
We are looking for a talented and detail-oriented Databricks Data Engineer / Cloud Data Engineer to join our data team. In this role, you will be responsible for building scalable data pipelines, transforming raw data into actionable insights, and optimizing data flows using Databricks and the modern data stack.
Responsibilities:
Design, develop, and maintain reliable and scalable data pipelines in Databricks (Apache Spark).
Work with structured and unstructured data sources, ingest data using tools like Delta Lake, Auto Loader, and Databricks Workflows.
Build and manage ETL/ELT processes (dbt, databricks, airflow) to support business intelligence, machine learning, and advanced analytics
Collaborate with data analysts, data scientists, and business stakeholders to understand data requirements.
Ensure data quality, integrity, and governance through validation and monitoring frameworks.
Implement version control (e.g., using Git and Databricks Repos).
Data pipeline monitoring and support using tools such as DBT, CloudWatch & Datadog
Query optimization of large datasets in Redshift and Databricks
Exposure to Continuous Integration / Continuous Delivery tools, such as BuildKite or Github Actions.
Qualifications:
2+ years of experience as a Data Engineer, preferably with Databricks.
Proficiency in PySpark, SQL, and Python.
Experience with cloud platforms (Azure, AWS, or GCP)
Familiarity with Delta Lake, Unity Catalog, and MLflow is a plus.
Strong understanding of data modeling, warehousing concepts, and performance optimization.
Bachelor's degree in Computer Science, Engineering, or a related field.
Share This Job:
