Databricks Data Engineer
Trebecon LLC
Charlotte, NC, United States
6 days ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
8 years minimum
Working hours
Regular working hours
Job source
Tech stack
Application Programming Interfaces (APIs)
Amazon Web Services
Microsoft Azure
Cloud Storage
Computer Programming
Databases
Data Architecture
Information Engineering
Data Governance
Extract Transform Load (ETL)
Data Transformation
Data Warehousing
+13 more
Python (Programming Language)
SQL Databases
Data Processing
Google Cloud
Sql Optimization
Apache Spark
Git
Data Layers
Data Lakes
Pyspark
Software Version Control
Data Pipelines
Databricks
Job description
- Design, develop, and maintain scalable ETL/ELT data pipelines using Databricks and PySpark.
- Build and optimize data processing solutions using Apache Spark, Python, and SQL.
- Implement Delta Lake tables and support schema evolution, data quality, and ACID transactions.
- Develop Bronze, Silver, and Gold data layers following the Medallion/Lakehouse architecture.
- Build batch and near-real-time data pipelines using Spark and Databricks.
- Develop and manage Databricks Jobs and Workflows.
- Integrate data from databases, APIs, cloud storage, and other enterprise data sources.
- Perform data transformation, cleansing, validation, and enrichment.
- Optimize Spark applications, SQL queries, and data pipelines for performance and cost.
- Implement data governance, security, and access controls using Unity Catalog.
- Monitor production pipelines, troubleshoot failures, and resolve data-quality issues.
- Collaborate with Data Architects, Analysts, Developers, and business stakeholders.
- Follow development best practices for version control, testing, deployment, and documentation.
Requirements
- 8+ years of experience in Data Engineering.
- Strong hands-on experience with Databricks.
- Strong proficiency in PySpark / Apache Spark.
- Advanced SQL skills.
- Strong programming experience with Python.
- Hands-on experience with Delta Lake.
- Experience with ETL/ELT pipeline development.
- Knowledge of Lakehouse and Medallion architecture.
- Experience with Databricks Workflows/Jobs.
- Experience with Unity Catalog and data governance.
- Strong understanding of data modeling and data warehousing concepts.
- Experience working with cloud platforms such as AWS, Azure, or Google Cloud Platform.
- Experience with Git and CI/CD practices.
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