Data Platform Engineer

On behalf of our Client from the USA, Mobilunity is looking for a Data Platform Engineer.
Our client develops software that supports companies working in commercial fire protection and mechanical services with managing their field operations and expanding their businesses. As a growing technology company, they value accountability, thoughtful choices, and creating a tangible impact. They bring together people who are curious, collaborative, and open to different perspectives, while giving them the independence and support to address meaningful challenges. From the start, you’ll be trusted with real responsibilities, encouraged to explore better ways of working, and given room to develop as your role and experience grow.
The position focuses on building and improving large-scale batch and streaming data pipelines with Python, SQL, and AWS services including DMS and Kinesis.
You’ll be responsible for shaping the architecture of cloud-based data platforms, developing efficient ETL/ELT processes, improving CI/CD and Infrastructure-as-Code practices, and supporting the growth of less experienced engineers. AI-assisted development tools will also be part of the engineering workflow, with a strong focus on maintaining reliability, performance, and data accuracy across the platform.
As part of the Data Platform team, you’ll work on critical batch and real-time data processing systems that support advanced analytics used by thousands of commercial contractors. The role provides full ownership of complex data solutions, from architectural decisions through implementation and ongoing optimization. You’ll also have the opportunity to introduce modern AI-assisted development approaches and help other engineers develop their technical skills in a collaborative, quality-focused environment.
About You
You take responsibility for the systems you work on and stay engaged until a problem is fully resolved. When an issue appears, you’re willing to investigate beyond your immediate area of responsibility to identify the underlying cause and make sure it is properly addressed.
You care about building reliable, maintainable solutions and continuously look for opportunities to improve system performance, scalability, and efficiency. You approach challenges proactively, focus on delivering results, and are motivated by creating solutions that provide a positive experience for customers.
Key Responsibilities:
Take the lead in developing, testing, and maintaining scalable Python solutions for data ingestion, transformation, and processing across both batch and streaming environments.
Create and improve data models and transformation processes that support advanced analytics and changing business intelligence requirements while maintaining strong data quality and performance.
Develop, optimize, and monitor high-throughput ETL/ELT pipelines using AWS DMS, Kinesis, and other data integration technologies.
Investigate data pipeline failures and performance issues, identify their underlying causes, and introduce preventative measures to improve reliability and protect data integrity.
Support junior engineers through mentoring and establish clear documentation practices for code, data models, and engineering processes to promote knowledge sharing and consistency.
Requirements:
Strong Data Engineering Background: Hands-on experience designing and developing data engineering solutions, performing thorough code reviews, and working with complex, large-scale ETL/ELT pipelines.
Cloud Data Platform Expertise: Extensive practical experience with enterprise cloud data platforms such as Amazon Redshift, Google BigQuery, or Snowflake, including knowledge of their architecture and approaches to performance optimization.
Advanced Programming Proficiency: Expert-level skills in Python and SQL (including advanced optimization techniques in MySQL, Postgres, and SQL Server), coupled with extensive experience with complex transformations and a strong command of AWS services (DMS, S3, Airflow, Kinesis, DocumentDB, CloudWatch, Kubernetes, Glue).
CI/CD & Infrastructure as Code: Experience designing and maintaining GitHub-based version control workflows and implementing advanced CI/CD processes for data infrastructure, together with a strong understanding of Infrastructure-as-Code practices and tooling.
AI-Assisted Engineering: Practical experience working with AI development tools such as Claude Code, GitHub Copilot, or Cursor, combined with the ability to validate, test, review, and take responsibility for AI-generated output.
Upper-intermediate to advanced English proficiency
In return we offer:
The friendliest community of like-minded IT-people
Open knowledge-sharing environment – exclusive access to a rich pool of colleagues willing to share their endless insights into the broadest variety of modern technologies
English classes in 1-to-1 & group modes with elements of gamification
Neverending fun: sports events, tournaments, music band, multiple affinity groups
Come on board, and let’s grow together!