Home › Companies › Fa Ewjt Saasfaprod1 Fa Ocs Oraclecloud Com Cx 2 › Senior 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
| Field | Value |
|---|---|
| Company | Fa Ewjt Saasfaprod1 Fa Ocs Oraclecloud Com Cx 2 |
| Title | Senior Databricks Engineer |
| Normalized title | - |
| Department / team | Data Analytics |
| Location | United States |
| Work model | - |
| Employment type | Full Time |
| Salary | - |
| Status | active |
| ATS provider | Oracle Recruiting Cloud / Fusion HCM |
| Posted / first seen | 2026-06-18 / 2026-06-19 |
| Changed / last seen | 2026-06-19 / 2026-06-19 |
Related slices
| Page | What it contains | Open |
|---|---|---|
| Company jobs | Active postings from Fa Ewjt Saasfaprod1 Fa Ocs Oraclecloud Com Cx 2. | Open |
| Company breakdowns | Role, location, ATS, and work model facets for this company. | Open |
| ATS provider jobs | Active postings observed through Oracle Recruiting Cloud / Fusion HCM. | Open |
| Provider filtered search | The same provider as a filtered job collection. | Open |
| Department jobs | Active postings in Data Analytics. | Open |
| Lifecycle events | Open, update, close, and reopen events for this posting. | Open |
| Original posting | Canonical source or apply URL captured from the ATS. | Open |
Linked records
| Company | Fa Ewjt Saasfaprod1 Fa Ocs Oraclecloud Com Cx 2 |
| Source | 907773df-d032-42dc-b60a-978734f5ac21 |
| ATS provider | Oracle 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 ID | 9b67a6e73ce0790aca127d1f3bb8afbdcf4021e2 |
| Org ID | 3ea3b397-9a23-408a-8421-50fd1d902746 |
| Source ID | 907773df-d032-42dc-b60a-978734f5ac21 |
| Board ID | 907773df-d032-42dc-b60a-978734f5ac21 |
| Provider | oracle_hcm |
| Provider Job Key | 12864 |
| Title | Senior Databricks Engineer |
| Normalized Title | — |
| Status | active |
| Active | yes |
| Location Text | United States; US New Jersey (JCO) C79 |
| Department | Data Analytics |
| Team | — |
| Employment Type | full_time |
| Workplace Type | — |
| Remote Policy | — |
| Country | United States |
| Region | — |
| City | — |
| Salary Raw | 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 |
| Salary Min | — |
| Salary Max | — |
| Salary Currency | — |
| Salary Period | — |
| Source URL | https://fa-ewjt-saasfaprod1.fa.ocs.oraclecloud.com/hcmUI/CandidateExperience/en/sites/cx_2/job/12864 |
| Apply URL | https://fa-ewjt-saasfaprod1.fa.ocs.oraclecloud.com/hcmUI/CandidateExperience/en/sites/cx_2/job/12864 |
| First Seen At | 2026-06-19 11:43:10Z |
| Last Seen At | 2026-06-19 11:43:10Z |
| Last Checked At | 2026-06-19 11:43:10Z |
| Last Changed At | 2026-06-19 11:43:10Z |
| Inactive At | — |
| Source Posted At | 2026-06-18 20:28:08Z |
| Source Updated At | — |
| Raw Payload Uri | s3://job-postings-prod-raw-590183727216/raw/provider=oracle_hcm/board=fa-ewjt-saasfaprod1.fa.ocs.oraclecloud.com|cx_2/date=2026-06-19/2026-06-19T11-41-22-240Z-e19cc1ad9c11f5a63cb8b01093caf729a83ba1c5adcb6a70539f4ca538a7b4c3.json |
Event Fields
{
"content_hash": "636f1cc12fc34df21c95bcaa175aca6dea9475d36893fa67a6e9ecc3df86c6cd",
"source_hash": "5c133d2f2266aef33d68c79e98df732cb856025173bcee84a9b802a3241082da",
"last_changed_at": "2026-06-19T11:43:10.690Z",
"active_status": "active"
}Parsed Structured
{
"language": "en",
"location": {
"raw": "United States",
"city": null,
"region": null,
"country": "United States",
"is_remote": false,
"confidence": 0.8
},
"salary_max": null,
"salary_min": null,
"inferred_at": "2026-06-19T11:43:10.164Z",
"launch_scope": {
"reason": "english_us_canada",
"included": true,
"language": "en",
"location": {
"raw": "United States",
"city": null,
"region": null,
"country": "United States",
"is_remote": false,
"confidence": 0.8
},
"countries": [
"United States"
]
},
"remote_policy": null,
"salary_period": null,
"workplace_type": null,
"salary_currency": null
}Extensions
{}Native Structured
{
"detail": {
"Id": "12864",
"Title": "Senior Databricks Engineer",
"media": [],
"skills": [],
"JobType": null,
"Category": "Data Analytics",
"JobGrade": null,
"JobLevel": null,
"JobShift": null,
"WorkDays": null,
"WorkHours": null,
"WorkYears": null,
"Department": null,
"HotJobFlag": false,
"StudyLevel": "Bachelor's Degree",
"WorkMonths": null,
"WorkerType": null,
"GeographyId": 300000000467584,
"JobFamilyId": 300001172146126,
"JobFunction": "Data Engineering",
"JobSchedule": "Full time",
"BusinessUnit": null,
"ContractType": null,
"Organization": null,
"TrendingFlag": true,
"workLocation": [
{
"Country": null,
"Region1": null,
"Region2": null,
"Region3": null,
"Building": null,
"Latitude": "40.72053",
"Longitude": "-74.04624",
"LocationId": 300000002980557,
"PostalCode": null,
"TownOrCity": null,
"AddressLine1": null,
"AddressLine2": null,
"AddressLine3": null,
"AddressLine4": null,
"LocationName": "US New Jersey (JCO) C79"
}
],
"ContentLocale": "en",
"HiringManager": null,
"LegalEmployer": null,
"RequisitionId": 300003030245699,
"WorkplaceType": "Work From Home",
"BusinessUnitId": 300000002965433,
"OrganizationId": 300000002988873,
"GeographyNodeId": 300001186829838,
"JobFunctionCode": "EXL_JFN_2007318629",
"LegalEmployerId": 300000002988873,
"PrimaryLocation": "United States",
"RequisitionType": "Professional",
"NumberOfOpenings": null,
"WorkplaceTypeCode": "ORA_REMOTE",
"BeFirstToApplyFlag": false,
"otherWorkLocations": [],
"secondaryLocations": [],
"ExternalContactName": null,
"ShortDescriptionStr": "Senior Databricks Engineer \nUS Remote\nWe 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.",
"ExternalContactEmail": null,
"ExternalPostedEndDate": null,
"OtherRequisitionTitle": null,
"requisitionFlexFields": [],
"ApplyWhenNotPostedFlag": false,
"DomesticTravelRequired": null,
"ExternalDescriptionStr": "<p>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.</p>",
"ObjectVerNumberProfile": "1",
"PrimaryLocationCountry": "US",
"CorporateDescriptionStr": "",
"ExternalPostedStartDate": "2026-06-18T20:28:08+00:00",
"ExternalQualificationsStr": "<ul><li>6+ Years of hands-on, progressive experience in Data Engineering, with at least 5 years focused heavily on the Databricks platform.</li><li>Architectural Understanding: Expert knowledge of Medallion Architecture, Data Vault 2.0 or Dimensional Modeling, and modern Lakehouse design patterns.</li><li>Scale Expertise: Proven track record of building and managing large-scale data infrastructure (Petabyte-scale) in cloud-native environments.</li><li>Industry Experience: Experience in the Insurance or Financial Services industry is preferred (focusing on claims, policy, or risk data).</li><li>Technical Toolset:<ul><li>Cloud Environment: Azure (preferred), AWS,.</li><li>Databricks Stack: Unity Catalog, Delta Live Tables, Databricks SQL, MLflow.</li><li>Core Languages: Expert-level SQL, Python, and PySpark.</li><li>Supporting Tools: dbt (Databricks adapter), Git, and Orchestration tools </li></ul></li></ul>",
"InternalQualificationsStr": "<ul><li>6+ Years of hands-on, progressive experience in Data Engineering, with at least 5 years focused heavily on the Databricks platform.</li><li>Architectural Understanding: Expert knowledge of Medallion Architecture, Data Vault 2.0 or Dimensional Modeling, and modern Lakehouse design patterns.</li><li>Scale Expertise: Proven track record of building and managing large-scale data infrastructure (Petabyte-scale) in cloud-native environments.</li><li>Industry Experience: Experience in the Insurance or Financial Services industry is preferred (focusing on claims, policy, or risk data).</li><li>Technical Toolset:<ul><li>Cloud Environment: Azure (preferred), AWS,.</li><li>Databricks Stack: Unity Catalog, Delta Live Tables, Databricks SQL, MLflow.</li><li>Core Languages: Expert-level SQL, Python, and PySpark.</li><li>Supporting Tools: dbt (Databricks adapter), Git, and Orchestration tools </li></ul></li></ul>",
"OrganizationDescriptionStr": "",
"primaryLocationCoordinates": [
{
"Latitude": "39.82844",
"Longitude": "-98.57939",
"CountryCode": "US",
"GeographyId": 300000000467584,
"GeographyNodeId": 300001186829838
}
],
"ExternalResponsibilitiesStr": "<p>Data Pipeline Development & Management</p><ul><li>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.</li><li>Workflow Orchestration: Develop and maintain sophisticated pipelines using Databricks Workflows or Airflow, focusing on modularity, reusability, and automated error handling.</li><li>Streaming & Real-time Integration: Implement real-time data flows utilizing Structured Streaming and Kafka/Event Hubs to enable immediate data availability for downstream consumption.</li><li>Data Security & Privacy: Enforce data anonymization and fine-grained access controls to ensure compliance with global regulations (GDPR/CCPA/HIPAA).</li><li>DataOps & DevOps: Implement CI/CD patterns using Databricks Asset Bundles (DABs), Terraform, and Git to automate environment parity and deployments.</li></ul><p>Data Ecosystem Management & Monitoring</p><ul><li>Open Table Formats: Manage and optimize Delta Lake storage, utilizing advanced features like Liquid Clustering, Z-Ordering, and Change Data Feed (CDF).</li><li>Compute Engine Optimization: Drive cost efficiency and performance by optimizing Spark configurations, Photon engine utilization, and Serverless SQL Warehouses.</li><li>Observability & Monitoring: Integrate comprehensive monitoring and alerting (e.g., Databricks System Tables, Grafana, or Splunk) to rapidly identify bottlenecks and troubleshoot production issues.</li></ul>",
"InternalResponsibilitiesStr": "<p>Data Pipeline Development & Management</p><ul><li>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.</li><li>Workflow Orchestration: Develop and maintain sophisticated pipelines using Databricks Workflows or Airflow, focusing on modularity, reusability, and automated error handling.</li><li>Streaming & Real-time Integration: Implement real-time data flows utilizing Structured Streaming and Kafka/Event Hubs to enable immediate data availability for downstream consumption.</li><li>Data Security & Privacy: Enforce data anonymization and fine-grained access controls to ensure compliance with global regulations (GDPR/CCPA/HIPAA).</li><li>DataOps & DevOps: Implement CI/CD patterns using Databricks Asset Bundles (DABs), Terraform, and Git to automate environment parity and deployments.</li></ul><p>Data Ecosystem Management & Monitoring</p><ul><li>Open Table Formats: Manage and optimize Delta Lake storage, utilizing advanced features like Liquid Clustering, Z-Ordering, and Change Data Feed (CDF).</li><li>Compute Engine Optimization: Drive cost efficiency and performance by optimizing Spark configurations, Photon engine utilization, and Serverless SQL Warehouses.</li><li>Observability & Monitoring: Integrate comprehensive monitoring and alerting (e.g., Databricks System Tables, Grafana, or Splunk) to rapidly identify bottlenecks and troubleshoot production issues.</li></ul>",
"InternationalTravelRequired": null
},
"list_job": {
"Id": "12864",
"Title": "Senior Databricks Engineer",
"JobType": null,
"Distance": 1781740800000,
"JobShift": null,
"Language": "US",
"WorkDays": null,
"JobFamily": null,
"Relevancy": 9,
"WorkHours": null,
"Department": null,
"HotJobFlag": false,
"PostedDate": "2026-06-18",
"StudyLevel": null,
"WorkerType": null,
"GeographyId": 300000000467584,
"JobFunction": null,
"JobSchedule": null,
"BusinessUnit": null,
"ContractType": null,
"ManagerLevel": null,
"Organization": null,
"TrendingFlag": true,
"workLocation": [
{
"Country": null,
"Region1": null,
"Region2": null,
"Region3": null,
"Building": null,
"Latitude": 40.72053,
"Longitude": -74.04624,
"LocationId": 300000002980557,
"PostalCode": null,
"TownOrCity": null,
"AddressLine1": null,
"AddressLine2": null,
"AddressLine3": null,
"AddressLine4": null,
"LocationName": "US New Jersey (JCO) C79"
}
],
"LegalEmployer": null,
"MediaThumbURL": null,
"WorkplaceType": "Work From Home",
"BusinessUnitId": 300000002965433,
"OrganizationId": 300000002988873,
"PostingEndDate": null,
"LegalEmployerId": 300000002988873,
"PrimaryLocation": "United States",
"WorkDurationYears": null,
"WorkplaceTypeCode": "ORA_REMOTE",
"BeFirstToApplyFlag": false,
"WorkDurationMonths": null,
"otherWorkLocations": [],
"secondaryLocations": [],
"ShortDescriptionStr": "Senior Databricks Engineer \nUS Remote\nWe 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.",
"requisitionFlexFields": [],
"DomesticTravelRequired": null,
"PrimaryLocationCountry": "US",
"ExternalQualificationsStr": null,
"ExternalResponsibilitiesStr": null,
"InternationalTravelRequired": null
},
"detail_meta": {
"url": "https://fa-ewjt-saasfaprod1.fa.ocs.oraclecloud.com/hcmRestApi/resources/latest/recruitingCEJobRequisitionDetails?expand=all&onlyData=true&finder=ById;Id=%2212864%22,siteNumber=cx_2",
"http_status": 200,
"content_type": "application/json",
"response_bytes": 9104
},
"detail_errors": []
}Get this page with API
Rendered from the bluedoor Job Postings API. Reproduce it:
GET https://api.bluedoor.sh/job-postings/v1/jobs/9b67a6e73ce0790aca127d1f3bb8afbdcf4021e2?include=descriptionJSONGET https://api.bluedoor.sh/job-postings/v1/orgs/3ea3b397-9a23-408a-8421-50fd1d902746JSONGET https://api.bluedoor.sh/job-postings/v1/sources/907773df-d032-42dc-b60a-978734f5ac21JSONGET https://api.bluedoor.sh/job-postings/v1/jobs/9b67a6e73ce0790aca127d1f3bb8afbdcf4021e2/eventsJSON