AssureSoft - Careers
Sr Data Engineer
Senior Data Engineer at AssureSoft, a LATAM software outsourcing company, who designs, builds, and maintains scalable ETL/ELT pipelines and data models, with data quality checks, monitoring, and performance optimization. Core stack: Python, SQL, dbt, Airbyte, Snowflake, and MySQL.
- Compensation
- Not disclosed
- Location
- LATAM
- Work setup
- Not specified
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 15+ years
- Category
- Data engineering
- Posted
Skills
Must have
- Solid professional experience in data engineering at a senior level
- Strong proficiency in Python for data processing, automation, and pipeline development
- Advanced SQL skills, including complex queries, transformations, and performance optimization
- Proven experience designing, developing, and maintaining ETL/ELT pipelines
- Hands-on experience with dbt for data transformation, modeling, testing, and documentation
- Practical experience with Airbyte for data ingestion, synchronization, and integration
- Strong experience with Snowflake, including data warehousing, modeling, and query optimization
- Experience with relational databases, particularly MySQL
- Solid understanding of data warehousing, dimensional modeling, and data pipeline architecture
- Experience implementing data quality validation, error handling, and pipeline monitoring
- Familiarity with Git, version control, and collaborative development workflows
- Experience with CI/CD pipelines and modern data engineering practices
- Hands-on experience using AI-assisted software development tools
- Strong debugging, troubleshooting, and analytical problem-solving skills
- Ability to work independently, collaborate effectively, and take ownership of deliverables
Nice to have
- Experience with cloud platforms (AWS, Azure, or Google Cloud), Docker, and modern data lake architectures
- Familiarity with Agile methodologies, data governance, security, and access control best practices
Full description
The key to our success is simple; we deliver the highest quality, on time, with passion and commitment, and live every day by a set of great values. We've built a company that fosters long-term careers in an environment of continuous learning, with cutting-edge benefits, tools, and resources. In addition, certifications that endorse our company as a great place to work.
Responsibilities
- Design, develop, test, and maintain scalable data pipelines and ETL/ELT processes.
- Build and optimize data transformation workflows using Python, SQL, and dbt.
- Develop and maintain data ingestion, synchronization, and integration pipelines using Airbyte.
- Design and optimize data models, transformations, and queries in Snowflake.
- Extract, transform, and integrate data from relational databases, including MySQL.
- Implement data quality checks, validation processes, error handling, and pipeline monitoring.
- Troubleshoot pipeline failures, perform root cause analysis, and implement sustainable solutions.
- Develop clean, reusable, maintainable, and well-documented code and SQL transformations.
- Collaborate with engineers, analysts, developers, and stakeholders to deliver reliable data solutions.
- Participate in technical estimation and development planning.
- Improve pipeline performance, scalability, reliability, and cost efficiency.
Requirements
- Solid professional experience in data engineering at a senior level.
- Strong proficiency in Python for data processing, automation, and pipeline development.
- Advanced SQL skills, including complex queries, data transformations, and performance optimization.
- Proven experience designing, developing, and maintaining ETL/ELT pipelines.
- Hands-on experience with dbt for data transformation, modeling, testing, and documentation.
- Practical experience with Airbyte for data ingestion, synchronization, and integration.
- Strong experience with Snowflake, including data warehousing, data modeling, and query optimization.
- Experience with relational databases, particularly MySQL.
- Solid understanding of data warehousing, dimensional modeling, and data pipeline architecture.
- Experience implementing data quality validation, error handling, and pipeline monitoring.
- Familiarity with Git, version control, and collaborative development workflows.