Must Have Technical/Functional Skills
10+ years of experience in Data Engineering, Data Warehousing, or Big Data development.
5+ years of hands-on experience with Databricks, Python, and PySpark.
Strong hands-on experience in Databricks, Python, and PySpark development.
Experience building and supporting large-scale ETL/ELT data pipelines.
Strong knowledge of Spark SQL, Delta Lake, and Data Lakehouse architecture.
Experience working with structured and unstructured data from multiple sources.
Strong SQL skills and experience with relational databases.
Experience with data modeling, data transformation, and data quality processes.
Knowledge of orchestration tools such as Airflow, ADF, or similar.
Experience with Git, CI/CD, and Agile development methodologies.
Strong analytical, debugging, and performance tuning skills.
Excellent verbal and written communication skills.
Roles Responsibilities
Design, develop, and maintain data pipelines using Databricks, Python, and PySpark.
Build scalable data ingestion, transformation, and integration solutions.
Collaborate with Data Architects, Analysts, and business teams to deliver data solutions.
Develop and optimize batch and real-time data processing workflows.
Ensure data quality, integrity, security, and governance standards are met.
Monitor, troubleshoot, and resolve production data pipeline issues.
Optimize Spark jobs, SQL queries, and Databricks workloads for performance.
Participate in data modeling, code reviews, and platform enhancement activities.
Create technical documentation and support production deployments.
Participate in Agile ceremonies and contribute to continuous improvement initiatives.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
- Dice Id: orcfeed
- Position Id: 24116_-1219421332832099172
- Posted 2 hours ago
