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HomeCompaniesFa Ewjt Saasfaprod1 Fa Ocs Oraclecloud Com Cx 2Senior Databricks Engineer

Senior Databricks Engineer

Fa Ewjt Saasfaprod1 Fa Ocs Oraclecloud Com Cx 2 · United States; US New Jersey (JCO) C79 · Active · Oracle Recruiting Cloud / Fusion HCM

Job facts

FieldValue
CompanyFa Ewjt Saasfaprod1 Fa Ocs Oraclecloud Com Cx 2
TitleSenior Databricks Engineer
Normalized title-
Department / teamData Analytics
LocationUnited States
Work model-
Employment typeFull Time
Salary-
Statusactive
ATS providerOracle Recruiting Cloud / Fusion HCM
Posted / first seen2026-06-18 / 2026-06-19
Changed / last seen2026-06-19 / 2026-06-19

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PageWhat it containsOpen
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ATS provider jobsActive postings observed through Oracle Recruiting Cloud / Fusion HCM.Open
Provider filtered searchThe same provider as a filtered job collection.Open
Department jobsActive postings in Data Analytics.Open
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Original postingCanonical source or apply URL captured from the ATS.Open

Linked records

CompanyFa Ewjt Saasfaprod1 Fa Ocs Oraclecloud Com Cx 2
Source907773df-d032-42dc-b60a-978734f5ac21
ATS providerOracle Recruiting Cloud / Fusion HCM

Description

Description We are seeking a high-caliber Senior Databricks Engineer to lead the architecture, development, and optimization of our next-generation Lakehouse platform. This is a critical role for a technical leader with 6+ years of deep data engineering expertise, specifically within the Databricks ecosystem. The ideal candidate will drive technical direction, establish robust data governance, and deliver high-impact, scalable data solutions that bridge the gap between raw data and actionable business intelligence. Responsibilities Data Pipeline Development & Management Ingestion & Transformation: Design and optimize high-volume ETL/ELT pipelines using Delta Live Tables (DLT) and PySpark, ensuring data integrity across the Bronze, Silver, and Gold layers. Workflow Orchestration: Develop and maintain sophisticated pipelines using Databricks Workflows or Airflow, focusing on modularity, reusability, and automated error handling. Streaming & Real-time Integration: Implement real-time data flows utilizing Structured Streaming and Kafka/Event Hubs to enable immediate data availability for downstream consumption. Data Security & Privacy: Enforce data anonymization and fine-grained access controls to ensure compliance with global regulations (GDPR/CCPA/HIPAA). DataOps & DevOps: Implement CI/CD patterns using Databricks Asset Bundles (DABs), Terraform, and Git to automate environment parity and deployments. Data Ecosystem Management & Monitoring Open Table Formats: Manage and optimize Delta Lake storage, utilizing advanced features like Liquid Clustering, Z-Ordering, and Change Data Feed (CDF). Compute Engine Optimization: Drive cost efficiency and performance by optimizing Spark configurations, Photon engine utilization, and Serverless SQL Warehouses. Observability & Monitoring: Integrate comprehensive monitoring and alerting (e.g., Databricks System Tables, Grafana, or Splunk) to rapidly identify bottlenecks and troubleshoot production issues. Qualifications 6+ Years of hands-on, progressive experience in Data Engineering, with at least 5 years focused heavily on the Databricks platform. Architectural Understanding: Expert knowledge of Medallion Architecture, Data Vault 2.0 or Dimensional Modeling, and modern Lakehouse design patterns. Scale Expertise: Proven track record of building and managing large-scale data infrastructure (Petabyte-scale) in cloud-native environments. Industry Experience: Experience in the Insurance or Financial Services industry is preferred (focusing on claims, policy, or risk data). Technical Toolset: Cloud Environment: Azure (preferred), AWS,. Databricks Stack: Unity Catalog, Delta Live Tables, Databricks SQL, MLflow. Core Languages: Expert-level SQL, Python, and PySpark. Supporting Tools: dbt (Databricks adapter), Git, and Orchestration tools

Full job record

Job ID9b67a6e73ce0790aca127d1f3bb8afbdcf4021e2
Org ID3ea3b397-9a23-408a-8421-50fd1d902746
Source ID907773df-d032-42dc-b60a-978734f5ac21
Board ID907773df-d032-42dc-b60a-978734f5ac21
Provideroracle_hcm
Provider Job Key12864
TitleSenior Databricks Engineer
Normalized Title
Statusactive
Activeyes
Location TextUnited States; US New Jersey (JCO) C79
DepartmentData Analytics
Team
Employment Typefull_time
Workplace Type
Remote Policy
CountryUnited States
Region
City
Salary RawDescription We are seeking a high-caliber Senior Databricks Engineer to lead the architecture, development, and optimization of our next-generation Lakehouse platform. This is a critical role for a technical leader with 6+ years of deep data engineering expertise, specifically within the Databricks ecosystem. The ideal candidate will drive technical direction, establish robust data governance, and deliver high-impact, scalable data solutions that bridge the gap between raw data and actionable business intelligence. Responsibilities Data Pipeline Development & Management Ingestion & Transformation: Design and optimize high-volume ETL/ELT pipelines using Delta Live Tables (DLT) and PySpark, ensuring data integrity across the Bronze, Silver, and Gold layers. Workflow Orchestration: Develop and maintain sophisticated pipelines using Databricks Workflows or Airflow, focusing on modularity, reusability, and automated error handling. Streaming & Real-time Integration: Implement real-time data flows utilizing Structured Streaming and Kafka/Event Hubs to enable immediate data availability for downstream consumption. Data Security & Privacy: Enforce data anonymization and fine-grained access controls to ensure compliance with global regulations (GDPR/CCPA/HIPAA). DataOps & DevOps: Implement CI/CD patterns using Databricks Asset Bundles (DABs), Terraform, and Git to automate environment parity and deployments. Data Ecosystem Management & Monitoring Open Table Formats: Manage and optimize Delta Lake storage, utilizing advanced features like Liquid Clustering, Z-Ordering, and Change Data Feed (CDF). Compute Engine Optimization: Drive cost efficiency and performance by optimizing Spark configurations, Photon engine utilization, and Serverless SQL Warehouses. Observability & Monitoring: Integrate comprehensive monitoring and alerting (e.g., Databricks System Tables, Grafana, or Splunk) to rapidly identify bottlenecks and troubleshoot production issues. Qualifications 6+ Years of hands-on, progressive experience in Data Engineering, with at least 5 years focused heavily on the Databricks platform. Architectural Understanding: Expert knowledge of Medallion Architecture, Data Vault 2.0 or Dimensional Modeling, and modern Lakehouse design patterns. Scale Expertise: Proven track record of building and managing large-scale data infrastructure (Petabyte-scale) in cloud-native environments. Industry Experience: Experience in the Insurance or Financial Services industry is preferred (focusing on claims, policy, or risk data). Technical Toolset: Cloud Environment: Azure (preferred), AWS,. Databricks Stack: Unity Catalog, Delta Live Tables, Databricks SQL, MLflow. Core Languages: Expert-level SQL, Python, and PySpark. Supporting Tools: dbt (Databricks adapter), Git, and Orchestration tools
Salary Min
Salary Max
Salary Currency
Salary Period
Source URLhttps://fa-ewjt-saasfaprod1.fa.ocs.oraclecloud.com/hcmUI/CandidateExperience/en/sites/cx_2/job/12864
Apply URLhttps://fa-ewjt-saasfaprod1.fa.ocs.oraclecloud.com/hcmUI/CandidateExperience/en/sites/cx_2/job/12864
First Seen At2026-06-19 11:43:10Z
Last Seen At2026-06-19 11:43:10Z
Last Checked At2026-06-19 11:43:10Z
Last Changed At2026-06-19 11:43:10Z
Inactive At
Source Posted At2026-06-18 20:28:08Z
Source Updated At
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