Data Engineer

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. \n 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