Senior data engineer (native databricks preferred)
Job Description
We are seeking a highly skilled
Senior Databricks Engineer / Architect
with hands‑on experience in
native Databricks environments
and a proven track record in
SAP to Databricks data migration
projects. The ideal candidate will be responsible for designing, implementing, and optimizing scalable data architectures that support advanced analytics, data engineering, and business intelligence initiatives.
Key Responsibilities
Design and architect scalable data platforms and pipelines within
native Databricks environments.
Lead and execute
SAP to Databricks migration
projects, ensuring seamless data integration and transformation.
Collaborate with business stakeholders, data engineers, and analysts to define architecture and data strategy.
Implement best practices for
data governance, security, and performance optimization
on the Databricks platform.
Develop and maintain
data models, ETL processes , and
automation frameworks
for high-performance analytics.
Guide and mentor technical teams on Databricks architecture, implementation standards, and platform utilization.
Work closely with cloud teams (Azure, AWS, or GCP) to ensure seamless integration with enterprise data ecosystems.
Stay current with Databricks feature releases and advancements to continuously enhance platform capabilities.
Requirements
Databricks Platform Architect Certification
(mandatory).
3+ years of hands‑on experience
working with
native Databricks environments.
Proven experience in
migrating data from SAP systems to Databricks.
Strong expertise in
Py Spark, SQL, Delta Lake, and Databricks Workflows.
Solid understanding of
data warehousing concepts, data modeling, and ELT/ETL design patterns.
Experience integrating Databricks with
cloud data platforms
(AWS S3, GCP Storage, or Azure).
Knowledge of
data governance, lineage, and security best practices.
Excellent problem‑solving, analytical, and communication skills.
Experience in
leading or architecting enterprise data solutions.
Senior Databricks Engineer / Architect
with hands‑on experience in
native Databricks environments
and a proven track record in
SAP to Databricks data migration
projects. The ideal candidate will be responsible for designing, implementing, and optimizing scalable data architectures that support advanced analytics, data engineering, and business intelligence initiatives.
Key Responsibilities
Design and architect scalable data platforms and pipelines within
native Databricks environments.
Lead and execute
SAP to Databricks migration
projects, ensuring seamless data integration and transformation.
Collaborate with business stakeholders, data engineers, and analysts to define architecture and data strategy.
Implement best practices for
data governance, security, and performance optimization
on the Databricks platform.
Develop and maintain
data models, ETL processes , and
automation frameworks
for high-performance analytics.
Guide and mentor technical teams on Databricks architecture, implementation standards, and platform utilization.
Work closely with cloud teams (Azure, AWS, or GCP) to ensure seamless integration with enterprise data ecosystems.
Stay current with Databricks feature releases and advancements to continuously enhance platform capabilities.
Requirements
Databricks Platform Architect Certification
(mandatory).
3+ years of hands‑on experience
working with
native Databricks environments.
Proven experience in
migrating data from SAP systems to Databricks.
Strong expertise in
Py Spark, SQL, Delta Lake, and Databricks Workflows.
Solid understanding of
data warehousing concepts, data modeling, and ELT/ETL design patterns.
Experience integrating Databricks with
cloud data platforms
(AWS S3, GCP Storage, or Azure).
Knowledge of
data governance, lineage, and security best practices.
Excellent problem‑solving, analytical, and communication skills.
Experience in
leading or architecting enterprise data solutions.