Senior Data Engineer
- Closed
- US Company | Small ( employees)
- LATAM (100% remote)
- 6+ years
- Short-term (40h)
- Analytics / Data
- Full Remote
Required skills
- AWS
- Azure
- Python
- ETL
- SQL
Requirements
Must-haves
- 6+ years of data engineering experience
- Proficiency Python for data processing (Pandas, PySpark)
- Proficiency AWS (S3, Glue, Redshift, Lambda)
- Expertise with SQL and relational databases (SQL Server)
- Experience building ETL processes handling millions of records
- Deep knowledge of data architecture, performance tuning, and governance practices
- Strong communication skills in both spoken and written English
Nice-to-haves
- Startup experience
- Experience with Azure (Data Factory, Synapse, Blob Storage) experience
- Experience in enterprise-scale environments with diverse data sources
- Familiarity with big data tools (Spark) and distributed processing
- Bachelor's Degree in Computer Engineering, Computer Science, or equivalent
What you will work on
This is a full-time role (40 hours/week) for a 7-12 month contract.
- Design, develop, and maintain scalable ETL pipelines for processing large datasets
- Build data infrastructure on AWS, Azure ensuring performance, scalability, and cost-effectiveness
- Develop and optimize data models and schemas for analytics and reporting
- Collaborate with analysts and stakeholders to understand data needs and deliver solutions
- Ensure data quality, integrity, and security throughout the lifecycle
- Monitor pipeline performance, troubleshoot bottlenecks, and resolve data issues
- Document processes and contribute to continuous improvement efforts across the team