Data Engineers @ Team Up IT Recruitment Remote

Data Engineers @ Team Up IT Recruitment

Remote

Core skills:

• Strong foundation in SQL and data modeling concepts. 
• Hands-on experience in data engineering, ETL/ELT processes, and pipeline development. 
• Familiarity with version control (Git) and CI/CD practices. 
• Experience working with cloud environments (AWS preferred). 
• Understanding of Agile methodologies and modern DevOps practices. 
• Strong analytical and problem-solving abilities with attention to detail and customer focus. 

Our client is expanding our Data Engineering Team to support a key global client with several high-priority data engineering and analytics initiatives.

This is a long-term project with opportunities to work on modern data platforms, cloud technologies, and advanced analytics solutions in a collaborative environments. 

Offer

• Long-term contract with a key global client. 
• Opportunity to work on cutting-edge cloud & data engineering platforms. 
• Collaborative, Agile working environment. 
• Competitive capped rates based on role. 

Requirements

Details on each roles:

1. Data Engineer – Trino Focus 

• Deep expertise in Starburst Trino / Apache Trino (installation, configuration, performance tuning). 
• Distributed query monitoring and troubleshooting. 
• Security frameworks (LDAP, Ranger). 
• Proficiency in Python, Bash, Node.js, Linux/Unix Shell. 
• Data engineering practices with GitHub Actions, Terraform, Kubernetes. 

2. Data Engineer – Matillion & SQL Focus

• Hands-on experience with Matillion (and sub-products). 
• Strong SQL skills; SQL Framework in HH knowledge preferred. 
• ELT process design and optimization. 

3. Data Engineer – dbt Focus

• Hands-on experience with dbt (model development, testing, deployment). 
• Experience with data warehousing solutions (Databricks, Redshift). 

,[ Design, build, and optimize data pipelines and integration solutions using tools such as Trino, Matillion, and dbt, ensuring scalability, reliability, and efficiency. , Develop and maintain cloud-based data platforms (primarily AWS, Databricks, Redshift), applying best practices in performance tuning, security, and monitoring. , Implement ELT/ETL processes and data models to support advanced analytics and business intelligence needs. , Apply DevOps and Agile practices (Git, CI/CD, Terraform, Kubernetes, GitHub Actions) for version control, automation, deployment, and release management. , Collaborate with cross-functional teams and stakeholders to align data solutions with business requirements, troubleshoot issues, and ensure customer-focused delivery. ] Requirements: Data engineering, Cloud, Data pipelines, dbt, AWS, Databricks, Redshift, Performance tuning, Security, ETL, Data models, DevOps, Git, CD, Terraform, Kubernetes, GitHub Actions, SQL, LDAP, Python, Bash, Node.js, Linux, Unix, Shell, Testing, Data analytics, AWS Redshift, AWS S3, Glue, AWS Lambda

Kategorie

data

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