Speedcast
DataEngineer
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Data Engineer at Speedcast. Skills: Data Engineering, AWS, Data Pipelines, Python. Design data solutions. Develop data solutions”
Industry & Context.
Analytical skills; Problem-solving skills
What They're Looking For.
Must Have
Commercial experience with Python, SQL skills, Experience using Git, Experience working within Agile/Scrum, Hands-on experience with AWS services, Understanding of AWS security best practices, Experience containerising applications using Docker, Experience developing and maintaining data pipelines, Understanding of data quality best practices, Understanding of data engineering best practices, Good understanding of SDLC, Analytical and problem-solving skills, Excellent communication skills, Excellent stakeholder management skills
Nice to Have
Advanced AWS expertise, Relevant AWS certifications, Experience designing analytical data models, Experience with Data Lakes, Experience with AWS Lake Formation, Experience with Data Lakehouse architectures, Experience with Bitbucket, Experience with Spark, Experience with PySpark, Understanding of MPP databases, Understanding of columnar storage technologies, Understanding of Parquet file formats, Experience with datasets, Experience with analytics tools, Experience with data visualisation tools, Experience with AWS deployment tools, Experience using Infrastructure as Code tools, Good understanding of GDPR, Good understanding of data governance principles, Experience supporting BI initiatives, Experience supporting Data Warehousing initiatives, Exposure to Data Science environments, Exposure to Machine Learning environments
What You'll Do.
Design data solutions
Develop data solutions
Maintain data solutions
Design data applications
Develop data applications
Test data applications
Maintain data applications
Design data pipelines
Develop data pipelines
Maintain data pipelines
Participate in Agile ceremonies
Participate in backlog grooming
Participate in sprint planning
Participate in prioritisation activities
Contribute to data architecture design
Implement data architecture design
Maintain data architecture design
Collaborate with data scientists
Collaborate with analysts
Collaborate with software engineers
Collaborate with business stakeholders
Deliver data-driven solutions
Monitor data platform performance
Implement performance improvements
Ensure data reliability
Ensure operational excellence
Evaluate new data technologies
Support adoption of new data technologies
Evaluate new data tools
Support adoption of new data tools
Evaluate new architectural approaches
Support adoption of new architectural approaches
Shape Data Warehousing vision
Execute Data Warehousing vision
Build cross-functional relationships
Understand data needs
Promote best practices in data engineering
Foster culture of continuous improvement
Participate in strategic planning
Define objectives for data initiatives
Define execution roadmaps for data initiatives
Communicate technical concepts
Communicate project progress
Foster collaborative team culture
How You'll Work.
Team & Collaboration
Data Engineering; Data Science; DevOps; Cross-functional relationships; Agile ceremonies; Product Managers
Communication Scope
Technical concepts; Project progress; Stakeholder management
Process & Methodology
Agile, Scrum, Backlog grooming, Sprint planning, Prioritisation
Full Job Description
Data Engineer **Job Title:** Data Engineer **Location:** Remote, Spain**** **Salary:** EUR 55,000-65,000 (depending on experience) **Overview of Position:** As a Data Engineer, you will play a pivotal role in shaping the infrastructure that handles the company's data assets, ensuring data flows efficiently and securely from source to insight. You will be part of a team responsible for designing, building, and maintaining scalable data pipelines and storage systems that support analytics and data-driven decision-making using AWS cloud technologies. The successful candidate will be capable of working independently, proactively driving improvements, and embracing new technologies throughout the product lifecycle. The role requires both a willingness to share knowledge and the ability to learn from other team members. This is a newly formed team supporting a new project, providing an opportunity to influence architectural decisions, challenge assumptions, and collaborate closely with colleagues across Data Engineering, Data Science, and DevOps. As part of a small, agile team, you may also contribute to reporting, dashboard creation, and other activities required to ensure project success. **What you will do:** * Design, develop, test, and maintain data solutions, applications, and data pipelines. * Participate in Agile ceremonies, backlog grooming, sprint planning, and prioritisation activities. * Contribute to the design, implementation, and maintenance of scalable, secure, compliant, and reliable data architectures. * Collaborate with data scientists, analysts, software engineers, and business stakeholders to deliver data-driven solutions. * Monitor data platform performance and implement improvements to optimise efficiency and reduce latency. * Actively ensure data quality, reliability, and operational excellence across data systems. * Evaluate and support the adoption of new data technologies, tools, and architectural approaches. * Help shape and execute the vision
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