Senior Data Engineer
TypeFull-time job
LocationTrinidad and Tobago
Posted1 hour ago
Location: Trinidad Tobago (Remote)
Job Type: Full-time
Job Summary:
A Senior Data Engineer is responsible for designing, building, and optimizing data infrastructure to support large-scale analytics and business intelligence.
Key Responsibilities:
Data Architecture & Pipeline Development Design and maintain scalable data pipelines for efficient data processing.
Database Management Oversee data storage solutions, ensuring reliability and performance.
Big Data Processing Work with technologies like Hadoop, Spark, and Kafka to handle large datasets.
Cloud Integration Implement data solutions on cloud platforms such as AWS, Azure, or Google Cloud.
Data Governance & Security Ensure compliance with data security standards and best practices.
Collaboration & Leadership Guide junior data engineers and work closely with data scientists and business teams.
Required Skills
Expertise in SQL, Python, Scala, or Java for data manipulation.
Experience with big data technologies (Hadoop, Spark, Kafka).
Strong knowledge of cloud computing platforms (AWS, Azure, GCP).
Advanced understanding of data modeling and database design.
Proficiency in ETL processes and workflow automation.
Ability to optimize data infrastructure for performance and scalability.
Familiarity with data governance, security protocols, and compliance.
Experience within banking industry is an asset.
Educational Requirements
A bachelors degree in computer science, software engineering, or a related technical field.
A masters degree can be beneficial for senior roles.
Certifications like AWS Certified Data Analytics Specialty or Google Professional Data Engineer can enhance qualifications.
Originally posted on Himalayas
Job Type: Full-time
Job Summary:
A Senior Data Engineer is responsible for designing, building, and optimizing data infrastructure to support large-scale analytics and business intelligence.
Key Responsibilities:
Data Architecture & Pipeline Development Design and maintain scalable data pipelines for efficient data processing.
Database Management Oversee data storage solutions, ensuring reliability and performance.
Big Data Processing Work with technologies like Hadoop, Spark, and Kafka to handle large datasets.
Cloud Integration Implement data solutions on cloud platforms such as AWS, Azure, or Google Cloud.
Data Governance & Security Ensure compliance with data security standards and best practices.
Collaboration & Leadership Guide junior data engineers and work closely with data scientists and business teams.
Required Skills
Expertise in SQL, Python, Scala, or Java for data manipulation.
Experience with big data technologies (Hadoop, Spark, Kafka).
Strong knowledge of cloud computing platforms (AWS, Azure, GCP).
Advanced understanding of data modeling and database design.
Proficiency in ETL processes and workflow automation.
Ability to optimize data infrastructure for performance and scalability.
Familiarity with data governance, security protocols, and compliance.
Experience within banking industry is an asset.
Educational Requirements
A bachelors degree in computer science, software engineering, or a related technical field.
A masters degree can be beneficial for senior roles.
Certifications like AWS Certified Data Analytics Specialty or Google Professional Data Engineer can enhance qualifications.
Originally posted on Himalayas
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