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# Spark / Databricks Platform Engineer

- **Company:** Resourcesoft, Inc.
- **Location:** Austin, TX, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Airflow, Big Data, Data Governance, Extract Transform Load (ETL), Data Warehousing, Database Storage Structures, Performance Tuning, Scala (Programming Language), SQL Databases, Data Ingestion, Apache Spark, Data Lakes, Pyspark, Dynamic Data, Data Pipelines, Databricks
- **Published:** July 28, 2026
- **Apply:** https://www.dice.com/job-detail/f886b7af-9aba-4878-9616-cf3a2c1947d5

## About the Role

* 8 or more years of experience in designing, developing, and deploying enterprise technology solutions.
 * Proficiency in PySpark, Scala, and SQL for large-scale data processing on Databricks.
 * Experience with building and optimizing ETL/ELT pipelines using Apache Spark and Delta Live Tables (DLT).
 * Experience in Delta Lake architectures, medallion designs (bronze/silver/gold), and lakehouse data modeling.
 * Experience with creating offline workflows and scheduling orchestration tasks using Lakeflow or Airflow.
 * Experience in native Databricks dashboard creation, data governance, and data security standards.
 * Excellent verbal and written communication skills.

## Description

* Design, develop, and optimize scalable data lakehouse solutions natively on the Databricks platform.
 * Build robust ETL/ELT ingestion pipelines utilizing PySpark, Delta Live Tables (DLT), and Spark engines.
 * Implement medallion architecture frameworks to structure and clean incoming enterprise datasets.
 * Formulate dimensional data models, star schemas, and gold-layer database structures for business intelligence.
 * Schedule and orchestrate offline data processing pipelines using Lakeflow Jobs or Airflow frameworks.
 * Create dynamic data visualizations and custom applications utilizing Databricks SQL dashboards and Databricks Apps.
 * Audit data quality, implement governance guardrails, and execute workload performance tuning to optimize cost.


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