Data Engineer (Milan Office, Remote)
We are looking for a
Data Engineer
to play a key role in shaping and scaling our platform as the organization grows in complexity and data maturity.
La preghiamo di leggere attentamente la seguente descrizione del lavoro per assicurarsi di essere la persona giusta per questo ruolo prima di candidarsi.In this role, you will be responsible for
designing and evolving
the core data infrastructure that powers analytics, machine learning, and critical business decisions. You will take
ownership
of how data flows across the company, from ingestion to consumption, ensuring it is reliable, well-modeled, and accessible to a wide range of stakeholders.
Key Responsibilities
Design, build, and maintain production-grade
data pipelines
and data-intensive systems
Configure, schedule, and monitor data pipeline execution to ensure
reliability ,
maintainability , and
timely
delivery across all data processes
Deploy and manage
data infrastructure on AWS or on-premises , ensuring scalability, security, and cost-efficiency
Monitor and optimize
relational and NoSQL database
performance (e.g., MySQL, PostgreSQL, MongoDB) to ensure efficient querying, indexing, and data access at scale
Ensure reliable ingestion, transformation, and availability of large-scale and time-series
financial data , considering financial-specific data quality characteristics.
Implement and maintain
data quality, validation, and monitoring
mechanisms across data workflows
Define and evolve
data models
and storage structures across relational and NoSQL systems
Collaborate with
Data Scientists and Analysts
to ensure accurate and efficient data access for analytics and modeling use cases
Optimize
data processing workflows
for performance, reliability, and operational stability
Troubleshoot
complex data issues and drive root cause analysis.
Contribute to
technical decision-making
and help define the roadmap for data infrastructure.
Requirements
Degree in Computer Science, Engineering, or a related field.
Strong programming skills in
Java or Python (or other JVM-based languages)
Strong understanding of
data modeling, SQL, and NoSQL databases
Strong focus on data quality, validation, and monitoring practices
Experience working with
large-scale and time-series datasets in financial contexts , with an understanding of their structure and common data quality challenges
Experience
building and maintaining production data pipelines or data-intensive systems,
with focus on reliability and performance
Ability to troubleshoot and optimize production data systems
Experience with
workflow orchestration and data pipeline scheduling tools
Solid understanding of financial data structures and concepts, with the ability to model and validate financial data accurately
Strong
problem-solving skills and attention to detail .
Professional
proficiency in English.
Premio Points
Experience with monitoring and visualization tools (e.g., dashboards)
Exposure to machine learning workflows and related data requirements
MDOTM Ltd (FRN: 824056) is an appointed representative of Thornbridge Investment Management LLP (FRN: 713859) which is authorised and regulated by the Financial Conduct Authority. xpavfwm
#J-18808-LjbffrPer questa posizione sono disponibili opzioni di lavoro da remoto/a casa.
Data Engineer
to play a key role in shaping and scaling our platform as the organization grows in complexity and data maturity.
La preghiamo di leggere attentamente la seguente descrizione del lavoro per assicurarsi di essere la persona giusta per questo ruolo prima di candidarsi.In this role, you will be responsible for
designing and evolving
the core data infrastructure that powers analytics, machine learning, and critical business decisions. You will take
ownership
of how data flows across the company, from ingestion to consumption, ensuring it is reliable, well-modeled, and accessible to a wide range of stakeholders.
Key Responsibilities
Design, build, and maintain production-grade
data pipelines
and data-intensive systems
Configure, schedule, and monitor data pipeline execution to ensure
reliability ,
maintainability , and
timely
delivery across all data processes
Deploy and manage
data infrastructure on AWS or on-premises , ensuring scalability, security, and cost-efficiency
Monitor and optimize
relational and NoSQL database
performance (e.g., MySQL, PostgreSQL, MongoDB) to ensure efficient querying, indexing, and data access at scale
Ensure reliable ingestion, transformation, and availability of large-scale and time-series
financial data , considering financial-specific data quality characteristics.
Implement and maintain
data quality, validation, and monitoring
mechanisms across data workflows
Define and evolve
data models
and storage structures across relational and NoSQL systems
Collaborate with
Data Scientists and Analysts
to ensure accurate and efficient data access for analytics and modeling use cases
Optimize
data processing workflows
for performance, reliability, and operational stability
Troubleshoot
complex data issues and drive root cause analysis.
Contribute to
technical decision-making
and help define the roadmap for data infrastructure.
Requirements
Degree in Computer Science, Engineering, or a related field.
Strong programming skills in
Java or Python (or other JVM-based languages)
Strong understanding of
data modeling, SQL, and NoSQL databases
Strong focus on data quality, validation, and monitoring practices
Experience working with
large-scale and time-series datasets in financial contexts , with an understanding of their structure and common data quality challenges
Experience
building and maintaining production data pipelines or data-intensive systems,
with focus on reliability and performance
Ability to troubleshoot and optimize production data systems
Experience with
workflow orchestration and data pipeline scheduling tools
Solid understanding of financial data structures and concepts, with the ability to model and validate financial data accurately
Strong
problem-solving skills and attention to detail .
Professional
proficiency in English.
Premio Points
Experience with monitoring and visualization tools (e.g., dashboards)
Exposure to machine learning workflows and related data requirements
MDOTM Ltd (FRN: 824056) is an appointed representative of Thornbridge Investment Management LLP (FRN: 713859) which is authorised and regulated by the Financial Conduct Authority. xpavfwm
#J-18808-LjbffrPer questa posizione sono disponibili opzioni di lavoro da remoto/a casa.