Data Engineer; Senior - ETL; Python+Snowflake - Remote, Latin América

Bluelight Software Consultancy

Bluelight is a leading software consultancy dedicated to designing and developing innovative technology that enhances users' lives. With a steadfast commitment to delivering exceptional service to our clients, Bluelight excels in its focus on quality and customer satisfaction. Our mission is not only to create cutting-edge applications but also to foster a collaborative and enriching work environment where each team member can grow and thrive.

With a presence across the United States and Central/South America, Bluelight is in an exciting phase of expansion, continually seeking exceptional talent to join its dynamic and diverse community.

We are looking for a skilled individual to join our rapidly growing team s position is ideal for someone who thrives in a fast-paced, dynamic environment where everyone's opinions and efforts are valued and appreciated. You will have the opportunity to contribute to challenging and meaningful projects, developing high-quality applications that stand out in the market. We value continuous learning, personal growth, and hard work, offering a collaborative environment that promotes professional development.

If you are passionate about software development and eager to be part of a growing software consultancy, we invite you to apply and join us on this exciting journey.

• Education & Experience
• Education:
  
  Bachelor's degree in Computer Science, Information Technology, Data Engineering, or a related field (or equivalent professional experience).
• Core
  
  Experience:
  
  Proven experience developing end-to-end data pipelines extracting/transforming/loading data from REST APIs, relational databases, cloud storage, and flat files.
• Snowflake Proficiency:
  Demonstrated hands-on experience with virtual warehouses, streams, tasks, stages, Snowpipe, secure data sharing, and performance optimization.
• SQL:
  Advanced SQL development skills with the ability to write complex queries, tune performance, and optimize large-scale workloads.
• Data Modeling:
  Experience with dimensional modeling techniques (star schemas, fact tables, dimension tables).
• Cloud & Dev Ops:
• Familiarity with cloud-based data ecosystems, particularly Microsoft Azure.
• Managing source code and CI/CD pipelines using Git and Azure Dev Ops (or similar).
• Soft Skills & Practices:
• Strong analytical, problem-solving, and detail-oriented mindset.
• Excellent verbal and written communication skills; ability to collaborate in a fast-paced environment with evolving priorities.
• Knowledge of data integration best practices, data governance, and enterprise data management.
• Preferred / Nice-to-Have
• Certifications:
  
  Snow Pro, Azure Data Engineer Associate, or equivalent cloud data platform certifications.
• Advanced Tech:
  Big data technologies, machine learning, data science platforms, or advanced analytics.
• BI Tools:
  Power BI, Tableau, or similar visualization platforms.
• Methodologies:
  Agile delivery frameworks and Dev Ops practices.
• Preferred Tech Stack Summary
• Core:
  Snowflake, Python/PySpark, SQL
• Cloud & Orchestration:
  Azure Data Lake Storage (ADLS), Azure Data Factory, Azure Key Vault
• Dev Ops & Infrastructure:
  Git, Azure Dev Ops, CI/CD, Infrastructure as Code (Terraform preferred)
• Integration & Analytics: REST APIs, Power BI

• Data Engineering & ETL Development
• Design, develop, and maintain scalable ETL/ELT pipelines using Python (PySpark), Snowflake, and cloud-native technologies.
• Build reliable, efficient, and reusable data ingestion, transformation, and loading processes.
• Snowflake Data Platform & Warehousing
• Utilize Snowflake's architecture to design, build, and optimize modern cloud data solutions.
• Implement and manage Snowflake objects (databases, schemas, tables, views, streams, tasks, stages, stored procedures).
• Leverage virtual warehouses, data sharing, time travel, and automated scaling to balance performance and cost efficiency.
• Apply dimensional modeling (star schemas, facts, dimensions) to build scalable enterprise data warehouses.
• Data Integration & Modeling
• Extract and ingest structured and semi-structured data from REST APIs, relational databases, SaaS apps, flat files, and cloud storage.
• Develop robust ingestion frameworks.
• Collaborate with data architects and stakeholders to create logical and physical data models aligned with business goals.
• Cloud Architecture & Standards
• Contribute to modern data platform concepts (data lakes, lake houses, data mesh architectures, enterprise data catalogs).
• Support integration between Snowflake and cloud-native services (primarily Azure).
• Establish and enforce data engineering standards and best practices.
• Quality, Governance & Security
• Implement automated data quality controls, validation frameworks, and monitoring processes.
• Support data governance initiatives and maintain adherence to organizational standards.
• Ensure data security, privacy, and regulatory compliance (access controls, masking policies, industry best practices).
• Optimization, Operations & Maintenance
• Monitor and…