Databricks Data Engineer -ERP systems (Oracle Fusion or EBS)-Houston (TX)- Onsite
Occupations:
Data Warehousing SpecialistsSoftware DevelopersDatabase ArchitectsComputer Systems Engineers/ArchitectsData ScientistsIndustries:
Web Search Portals, Libraries, Archives, and Other Information ServicesWired and Wireless Telecommunications (except Satellite)Satellite TelecommunicationsEducational Support ServicesSoftware PublishersDuration :12+ MonthsWe are seeking an experienced Databricks Data Engineer who can play a crucial role in our Fintech data lake project.What You Bring- 7+ years of experience working in data warehousing systems, with 2+ years experience working in building reporting solutions for ERP systems (Oracle Fusion or EBS)- 3+ strong hands-on programming expertise in Databricks landscape, including SparkSQL, Workflows for data processing and pipeline development- 3+ strong hands-on data transformation/ETL skills using Spark SQL, Pyspark, Unity Catalog working in Databricks Medallion architecture- 2+ yrs work experience in one of cloud platforms: Azure, AWS or GCP- Experience working in using Git version control, and well versed with CI/CD best practices to automate the deployment and management of data pipelines and infrastructure- Hands-on experience building data ingestion pipelines from ERP systems (Oracle Fusion preferably) to a Databricks environment, using Fivetran or any alternative data connectors- Experience in a fast-paced, ever-changing and growing environment- Understanding of metadata management, data lineage, and data glossaries is a plus- Must have report development experience using PowerBI, SplashBI or any enterprise reporting toolWhat You'll Do- Involve in design and development of enterprise data solutions in Databricks, from ideation to deployment, ensuring robustness and scalability.- Work with the Data Architect to build, and maintain robust and scalable data pipeline architectures on Databricks using PySpark and SQL- Assemble and process large, complex ERP datasets to meet diverse functional and non-functional requirements.- Involve in continuous optimization efforts, implementing testing and tooling techniques to enhance data solution quality- Focus on improving performance, reliability, and maintainability of data pipelines.- Implement and maintain PySpark and databrick SQL workflows for querying and analyzing large datasets- Involve in release management using Git and CI/CD practices- Develop business reports using SplashBI reporting tool leveraging the data from Databricks gold layerQualifications- Bachelors Degree in Computer Science, Engineering, Finance or equivalent experience- Good communication skills