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

• 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, lakehouses, 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 optimize Snowflake workloads, ETL/ELT processes, and SQL queries to meet SLAs. • Analyze warehouse utilization and recommend performance and cost-efficiency improvements. • Monitor pipelines, diagnose performance issues, and implement long-term solutions; support production environments and incident resolution. • Maintain comprehensive documentation for pipelines, flows, transformations, data models, and operational processes. • Collaboration • Partner with cross-functional teams (data architects, data scientists, analysts, business stakeholders) to understand requirements and provide technical expertise.

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 at Bluelight. This 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. What we are looking for • 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 & DevOps: • Familiarity with cloud-based data ecosystems, particularly Microsoft Azure. • Managing source code and CI/CD pipelines using Git and Azure DevOps (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: SnowPro, 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 DevOps practices. • Preferred Tech Stack Summary • Core: Snowflake, Python/PySpark, SQL • Cloud & Orchestration: Azure Data Lake Storage (ADLS), Azure Data Factory, Azure Key Vault • DevOps & Infrastructure: Git, Azure DevOps, CI/CD, Infrastructure as Code (Terraform preferred) • Integration & Analytics: REST APIs, Power BI Responsibilities • 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, lakehouses, 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 optimize Snowflake workloads, ETL/ELT processes, and SQL queries to meet SLAs. • Analyze warehouse utilization and recommend performance and cost-efficiency improvements. • Monitor pipelines, diagnose performance issues, and implement long-term solutions; support production environments and incident resolution. • Maintain comprehensive documentation for pipelines, flows, transformations, data models, and operational processes. • Collaboration • Partner with cross-functional teams (data architects, data scientists, analysts, business stakeholders) to understand requirements and provide technical expertise. Company Benefits • Competitive salary and bonuses, including performance-based salary increases. • Generous paid-time-off policy • Flexible working hours • Work remotely • Continuing education, training, confe