Digital Transformation Project
Young and international culture
AI initiative
Role SummaryWe are seeking an experienced
Engineer
to play a key role in the migration of our on‑premise / legacy data warehouse to
Oracle Cloud Infrastructure (OCI) . This role will also contribute to
AI‑oriented initiatives , enabling advanced analytics, machine learning, and data‑driven decision‑making across the organization.
The ideal candidate combines strong data engineering fundamentals with cloud migration experience and a modern mindset toward AI, automation, and scalable analytics architectures.
Key ResponsibilitiesData Warehouse Migration & Modernization
Lead and execute the migration of enterprise data warehouse solutions to
Oracle Cloud (OCI) , ensuring data integrity, performance, and security
Design and implement cloud‑native data architectures using
Oracle Autonomous Data Warehouse (ADW) , Object Storage, and related OCI services
Refactor and optimize existing ETL/ELT pipelines for cloud scalability and cost efficiency
Migrate and modernize legacy SQL, PL/SQL, and BI workloads for cloud‑based analytics
Collaborate with architecture, infrastructure, and security teams to align with cloud standards and governance
Data Engineering & Platform Development
Design and develop reliable, scalable data pipelines for structured and semi‑structured data
Implement data quality checks, lineage, and monitoring to ensure trusted datasets
Support near real‑time and batch processing use cases as required
Optimize query performance, data models, and storage strategies in Oracle Cloud
Develop reusable data frameworks and automation scripts for repeatable deployments
AI & Advanced Analytics Enablement
Enable AI/ML use cases by preparing high‑quality, analytics‑ready datasets
Partner with data scientists and analytics teams to operationalize machine learning models
Support feature engineering, data versioning, and model training pipelines
Integrate AI‑driven insights into downstream analytics, dashboards, or applications
Leverage Oracle Cloud AI/ML services or open‑source ML frameworks where appropriate
Collaboration & Delivery
Work closely with business stakeholders, BI teams, and data science teams to translate requirements into data solutions
Contribute to agile delivery cycles, including sprint planning, estimations, and code reviews
Document architecture, data flows, and operational procedures
Mentor junior engineers and promote data engineering best practices
Required Qualifications
Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field
5+ years of experience in
data engineering, data warehousing, or analytics engineering
Hands‑on experience with
Oracle databases
(e.g., Oracle DW, PL/SQL, SQL performance tuning)
Proven experience migrating data platforms to
Oracle Cloud Infrastructure (OCI)
or similar cloud environments
Strong expertise in
ETL/ELT design , data modeling (dimensional, data vault, or similar), and SQL
Experience building and maintaining production‑grade data pipelines
Solid understanding of cloud security, networking, and data governance concepts
AI & Modern Analytics Experience (Required / Strongly Preferred)
Experience supporting
AI/ML or advanced analytics initiatives
Familiarity with machine learning data preparation, feature engineering, and model deployment workflows
Exposure to Python, Spark, or similar data processing frameworks
Understanding of MLOps or data platforms that support AI lifecycle management
Nice to Have
Experience with
Oracle Autonomous Database , OCI Data Integration, OCI Data Science, or OCI AI services
Knowledge of open‑source tools (e.g., Airflow, dbt, Spark)
Experience with BI tools and analytics platforms (e.g., Oracle Analytics, Power BI, Tableau)
Cloud certifications (Oracle Cloud, AWS, Azure, or GCP)
Experience working in large‑scale transformation or modernization programs
What Success Looks Like
Successful migration of legacy data warehouse workloads to OCI with minimal disruption
Improved performance, scalability, and reliability of data platforms
High‑quality, AI‑ready datasets enabling advanced analytics and machine learning use cases
Strong collaboration across engineering, analytics, and business teams
Adoption of modern data engineering and cloud best practices
#J-18808-Ljbffr
Young and international culture
AI initiative
Role SummaryWe are seeking an experienced
Engineer
to play a key role in the migration of our on‑premise / legacy data warehouse to
Oracle Cloud Infrastructure (OCI) . This role will also contribute to
AI‑oriented initiatives , enabling advanced analytics, machine learning, and data‑driven decision‑making across the organization.
The ideal candidate combines strong data engineering fundamentals with cloud migration experience and a modern mindset toward AI, automation, and scalable analytics architectures.
Key ResponsibilitiesData Warehouse Migration & Modernization
Lead and execute the migration of enterprise data warehouse solutions to
Oracle Cloud (OCI) , ensuring data integrity, performance, and security
Design and implement cloud‑native data architectures using
Oracle Autonomous Data Warehouse (ADW) , Object Storage, and related OCI services
Refactor and optimize existing ETL/ELT pipelines for cloud scalability and cost efficiency
Migrate and modernize legacy SQL, PL/SQL, and BI workloads for cloud‑based analytics
Collaborate with architecture, infrastructure, and security teams to align with cloud standards and governance
Data Engineering & Platform Development
Design and develop reliable, scalable data pipelines for structured and semi‑structured data
Implement data quality checks, lineage, and monitoring to ensure trusted datasets
Support near real‑time and batch processing use cases as required
Optimize query performance, data models, and storage strategies in Oracle Cloud
Develop reusable data frameworks and automation scripts for repeatable deployments
AI & Advanced Analytics Enablement
Enable AI/ML use cases by preparing high‑quality, analytics‑ready datasets
Partner with data scientists and analytics teams to operationalize machine learning models
Support feature engineering, data versioning, and model training pipelines
Integrate AI‑driven insights into downstream analytics, dashboards, or applications
Leverage Oracle Cloud AI/ML services or open‑source ML frameworks where appropriate
Collaboration & Delivery
Work closely with business stakeholders, BI teams, and data science teams to translate requirements into data solutions
Contribute to agile delivery cycles, including sprint planning, estimations, and code reviews
Document architecture, data flows, and operational procedures
Mentor junior engineers and promote data engineering best practices
Required Qualifications
Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field
5+ years of experience in
data engineering, data warehousing, or analytics engineering
Hands‑on experience with
Oracle databases
(e.g., Oracle DW, PL/SQL, SQL performance tuning)
Proven experience migrating data platforms to
Oracle Cloud Infrastructure (OCI)
or similar cloud environments
Strong expertise in
ETL/ELT design , data modeling (dimensional, data vault, or similar), and SQL
Experience building and maintaining production‑grade data pipelines
Solid understanding of cloud security, networking, and data governance concepts
AI & Modern Analytics Experience (Required / Strongly Preferred)
Experience supporting
AI/ML or advanced analytics initiatives
Familiarity with machine learning data preparation, feature engineering, and model deployment workflows
Exposure to Python, Spark, or similar data processing frameworks
Understanding of MLOps or data platforms that support AI lifecycle management
Nice to Have
Experience with
Oracle Autonomous Database , OCI Data Integration, OCI Data Science, or OCI AI services
Knowledge of open‑source tools (e.g., Airflow, dbt, Spark)
Experience with BI tools and analytics platforms (e.g., Oracle Analytics, Power BI, Tableau)
Cloud certifications (Oracle Cloud, AWS, Azure, or GCP)
Experience working in large‑scale transformation or modernization programs
What Success Looks Like
Successful migration of legacy data warehouse workloads to OCI with minimal disruption
Improved performance, scalability, and reliability of data platforms
High‑quality, AI‑ready datasets enabling advanced analytics and machine learning use cases
Strong collaboration across engineering, analytics, and business teams
Adoption of modern data engineering and cloud best practices
#J-18808-Ljbffr