Xinova Group
Direct message the job poster from Xinova Group
Type:
Contract-to-Hire Start Date:
January Company Size:
~10,000 employees Revenue:
~$10B About the Role
A Fortune 500 real estate organization is seeking a mid–senior level
Databricks Engineer
to support a major data modernization initiative. This engineer will play a key role in transforming legacy and outdated data platforms into modern, scalable cloud-based solutions. The ideal candidate is both highly technical and strong in theoretical understanding (50/50 split). Responsibilities
Design, build, and optimize ETL/ELT pipelines using
PySpark ,
Spark SQL , and
Databricks . Migrate large-scale data workloads from legacy/on‑prem systems to
Azure
cloud data platforms. Develop and maintain data workflows using
Azure Data Factory . Work with
T‑SQL
to manipulate, transform, and analyze data within relational database environments. Collaborate with cross‑functional teams to implement best practices around data engineering, governance, and architecture. Strong communication skills with technical and non‑technical stakeholders. Contribute to architectural discussions around cloud strategy, data modeling, and transformation patterns. Troubleshoot performance issues and optimize pipelines for scalability and cost‑efficiency. Required Skills & Experience
5+ years
of professional experience in data engineering. Practical Databricks experience , including notebook development, cluster management, and job orchestration. Advanced T‑SQL
skills — ability to write complex queries, stored procedures, and optimise performance. Experience with
Azure Data Factory
(pipelines, data flows, integration runtime). Familiarity with
Spark SQL
and distributed data processing. Experience working with datasets similar to
AdventureWorks
or enterprise‑scale relational environments. Strong understanding of modern cloud data architectures and transformation patterns. Nice to Have
Experience migrating from legacy/on‑prem SQL systems to Azure cloud. Performance tuning in Spark and SQL. Familiarity with Delta Lake and Azure storage services. Seniority level
Mid‑Senior level Employment type
Full‑time Job function
IT System Data Services
#J-18808-Ljbffr
Contract-to-Hire Start Date:
January Company Size:
~10,000 employees Revenue:
~$10B About the Role
A Fortune 500 real estate organization is seeking a mid–senior level
Databricks Engineer
to support a major data modernization initiative. This engineer will play a key role in transforming legacy and outdated data platforms into modern, scalable cloud-based solutions. The ideal candidate is both highly technical and strong in theoretical understanding (50/50 split). Responsibilities
Design, build, and optimize ETL/ELT pipelines using
PySpark ,
Spark SQL , and
Databricks . Migrate large-scale data workloads from legacy/on‑prem systems to
Azure
cloud data platforms. Develop and maintain data workflows using
Azure Data Factory . Work with
T‑SQL
to manipulate, transform, and analyze data within relational database environments. Collaborate with cross‑functional teams to implement best practices around data engineering, governance, and architecture. Strong communication skills with technical and non‑technical stakeholders. Contribute to architectural discussions around cloud strategy, data modeling, and transformation patterns. Troubleshoot performance issues and optimize pipelines for scalability and cost‑efficiency. Required Skills & Experience
5+ years
of professional experience in data engineering. Practical Databricks experience , including notebook development, cluster management, and job orchestration. Advanced T‑SQL
skills — ability to write complex queries, stored procedures, and optimise performance. Experience with
Azure Data Factory
(pipelines, data flows, integration runtime). Familiarity with
Spark SQL
and distributed data processing. Experience working with datasets similar to
AdventureWorks
or enterprise‑scale relational environments. Strong understanding of modern cloud data architectures and transformation patterns. Nice to Have
Experience migrating from legacy/on‑prem SQL systems to Azure cloud. Performance tuning in Spark and SQL. Familiarity with Delta Lake and Azure storage services. Seniority level
Mid‑Senior level Employment type
Full‑time Job function
IT System Data Services
#J-18808-Ljbffr