
Data Solutions Engineer
4 days ago
About our team
We are a group of professionals who work on building and deploying data pipelines using Python and PySpark. Our goal is to deliver scalable cloud-based data solutions that directly impact the business.
Our ideal candidate is someone who enjoys rolling up their sleeves, building robust data pipelines, and delivering results. This person thrives on execution, values doing over discussing, and prefers outcomes over process.
Key Responsibilities:- Build, deploy, and manage data pipelines using Python and PySpark
- Develop and optimize ETL/ELT processes to support data integration across systems
- Work directly with GCP and AWS services to implement scalable cloud-based data solutions
- Own data workflows end-to-end — from ingestion to transformation to storage
- Continuously monitor and improve pipeline reliability, speed, and data quality
- Use GenAI and automation tools to speed up development and reduce manual effort
- Proactively debug, troubleshoot, and resolve data engineering issues
- Ensure data is available and trustworthy for analytics and downstream systems
- Strong proficiency in Python and PySpark
- Working experience with cloud platforms like GCP and/or AWS
- Solid understanding of ETL/ELT, data warehouse, and data lake concepts
- Proficient in working with relational databases—preferably PostgreSQL and MySQL—as well as non-relational databases, with a focus on MongoDB
- Driven by delivery and results — you get things done efficiently
- Self-starter attitude with minimal need for hand-holding
- Excitement for automating work using GenAI or scripting tools
- Familiarity with SCD, CDC, Real-time Streaming vs Batch-processing
We offer high-impact role where execution speed is valued and recognised
We give freedom to build, ship, and iterate without red tape
We have lean, high-performing data team
We provide opportunities to innovate with Generative AI tools
We are fast learning environment and ownership from day one
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