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 for Business Intelligence and Data Warehousing across the organisation.
Build cross-functional relationships with Data Scientists, Product Managers, Software Engineers, and business stakeholders to understand and meet data needs.
Promote best practices in data engineering and foster a culture of continuous improvement.
Participate in strategic planning for data initiatives, helping define objectives and execution roadmaps.
Communicate complex technical concepts and project progress to both technical and non-technical audiences.
Mentor and support team members where appropriate.
Foster a collaborative team culture built on transparency, accountability, and growth.
What we need from you:
Commercial experience with Python.
Strong SQL skills (any major SQL dialect).
Experience using Git for source control and version management.
Experience working within Agile/Scrum environments.
Hands-on experience with AWS services.
Understanding of AWS security best practices for data-related products.
Experience containerising applications using Docker.
Experience developing and maintaining data pipelines.
Understanding of data quality, data governance, and data engineering best practices.
Good understanding of the software development lifecycle (SDLC).
Strong analytical and problem-solving skills.
Excellent communication and stakeholder management skills.
Even better if you have:
Advanced AWS expertise, including relevant AWS certifications.
Experience designing analytical data models, particularly Kimball-style star schemas.
Experience with Data Lakes and AWS Lake Formation.
Experience with Data Lakehouse architectures.
Experience with Bitbucket.
Experience with Spark and PySpark.
Understanding of MPP databases, columnar storage technologies, and Parquet file formats.
Experience with datasets, analytics, and data visualisation tools.
Experience with AWS deployment tools such as CodePipeline and CodeDeploy.
Experience using Infrastructure as Code tools such as CloudFormation.
Good understanding of GDPR and data governance principles.
Experience supporting Business Intelligence and Data Warehousing initiatives.
Exposure to Data Science or Machine Learning environments.
Working at Speedcast:
Find great opportunities to make an impact. We have a "one team, one dream" mentality. We work together to make great things happen. Working at Speedcast isn't just a job,
Benefits
Vision insuranceRemote work options
Additional Information
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.
Speedcast · Remote