Oracle Fusion HCM Data Engineer; C2H

Manager
- Recruitment @ Compunnel Inc. | HR Business Partnering

Experience

Required:

10+ years in Oracle Fusion HCM

An Oracle Engineer with Oracle Fusion experience and Databricks is responsible for designing, developing, and maintaining scalable and efficient data solutions that integrate data from various sources including Oracle Fusion applications and process it within the Databricks environment.

• Design, build, and optimize robust ELT pipelines to ingest, transform, and load data from Oracle Fusion applications and other sources into the Databricks Lakehouse. This involves using PySpark, SQL, and Databricks notebooks.
• Leverage Databricks functionalities such as Delta Lake, Unity Catalog, and Spark optimization techniques to ensure data quality, performance, and governance.
• Develop connectors and integration strategies to extract data from Oracle Fusion modules (e.g., Financials, HCM, SCM) using APIs, SQL, or other methods.
• Design and implement data models within Databricks, potentially following a medallion architecture, to support analytical and reporting requirements.
• Tune Spark jobs and optimize data processing within Databricks for efficiency and cost-effectiveness.
• Implement data quality checks, error handling, and data validation frameworks to ensure data integrity, and adhere to data governance policies and security best practices.
• Work closely with data architects, data scientists, business analysts, and other stakeholders to understand data requirements and deliver solutions that meet business needs.
• Develop automation scripts and implement CI/CD pipelines for Databricks workflows and deployments.
• Provide operational support, troubleshoot data-related issues, and perform root cause analysis.

• Strong proficiency in Databricks, including PySpark, Scala, Delta Lake, Unity Catalog, and Databricks notebooks.
• Experience with Oracle Fusion, knowledge of its data structures, APIs, and data extraction methods.
• Expertise in SQL for querying, manipulating, and optimizing data in both Oracle and Databricks.
• Familiarity with a major cloud provider (e.g., AWS, Azure, GCP) where Databricks is deployed.
• Data Warehousing and ETL/ELT concepts; solid understanding of data warehousing principles and experience building and optimizing data pipelines.
• Problem-solving and analytical skills; ability to analyze complex data issues and propose effective solutions.
• Communication and collaboration; strong interpersonal skills to work effectively within cross-functional teams.

• Mid‑Senior level

• Contract

• Information Technology

• IT Services and IT Consulting