Data Engineer (Databricks)
Skills
About the role
Key Responsibilities:
Transform and clean data using SQL & Python in Databricks
Build dashboards using Power BI / Tableau
Ensure data quality and consistency
Collaborate with stakeholders to deliver insights
Create documentation for data workflows and dashboards
Data Pipeline Development: Design, build, and maintain scalable ETL/ELT processes using Databricks and Spark.
Spark Optimization: Tune and optimize Spark jobs and data transformations for performance.
Lakehouse Architecture: Implement data reliability, governance, and security using Delta Lake and Unity Catalog.
Workflow Orchestration: Automate data workflows using Databricks Workflows or tools such as Airflow.
Collaboration: Work with analysts and business stakeholders.
Requirements:
Strong SQL and Python skills
Experience with dashboarding tools (Power BI/Tableau)
Familiarity with Databricks or big data platforms
Languages: PySpark, SQL.
Databricks Features: Delta Lake, Structured Streaming, Delta Live Tables (DLT).
Cloud Platforms: AWS, Azure, or GCP.
DevOps: Git, Terraform, CI/CD practices.
Tools: Databricks Notebooks, Databricks Repos.
Good to Have:
Spark / PySpark
Git, JIRA, or QA/testing experience
Pay: Up to $7,000.00 per month
Experience:
Databricks: 3 years (Required)
Work Location: In person
Questions about this role
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