CloudGeometry
14/05/2025
We are looking for a Senior Data Engineer/Architect with extensive hands-on experience in the Databricks ecosystem and exceptional communication skills to join our flagship project: a cutting-edge Data Platform for the life sciences industry. This platform supports industry leaders such as Pfizer, Moderna, and Novartis in developing innovative RNA-based solutions, leveraging data-driven research, cloud computing, and advanced AI capabilities. This role offers a unique opportunity for an experienced data engineer to take the next step in their career, playing a key technical leadership role in the rapidly evolving world of AI-driven solutions.
Responsibilities
- Design, develop, and optimize data pipelines and workflows within the Databricks platform.
- Lead architecture discussions with engineering, product managers, and data scientists to implement advanced analytics solutions that drive business insights.
- Build, optimize, and fine-tune Databricks workflows to improve performance and reliability.
- Work closely with data scientists and analysts to ensure data quality.
- Ensure the integrity, accuracy, and security of data across all processing stages.
- Implement data ingestion from various sources into Databricks, ensuring data quality and reliability.
- Participate in daily Scrum ceremonies and collaborate with team members in the US and Europe, with required online presence from 9 AM to 5 PM EST (for candidates in Europe until 1 PM EST).
Qualifications
- Bachelor’s degree in Computer Science, Engineering, or a related field; Master’s degree preferred.
- 8+ years of experience in software development, preferably in data engineering, data warehousing, or data analytics teams.
- 5+ years of experience with the DataBricks ecosystem.
- Expertise in Python and TypeScript.
- Hands-on experience with Lake House architecture.
- Experience with Spark/Glue, Delta tables, and Iceberg.
- Proven ability to design and implement scalable data pipelines/ETL processes using Databricks.
- Knowledge of cloud-based data storage and processing technologies, especially AWS services like S3, Step Functions, Lambda, and Airflow.
- Familiarity with CI/CD practices, version control (Git), automated testing, and Agile methodologies.
- Experience working in US-led high-tech companies and startups.
Nice to Have
- DataBricks certifications.
- AWS or Azure DevOps or SA certifications.
- Knowledge of DevOps and MLOps principles.
- Experience working with Data Scientists and ML Developers.
- Leadership experience in technology services companies.