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. 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).
- 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
- Integration & Analytics: REST APIs, Power BI Responsibilities
- 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.
- Collaborate with data architects and stakeholders to create logical and physical data models aligned with business goals.
- 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.
- 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
- Work remotely
- Continuing education, training, conferences
- Company-sponsored coursework, exams, and certificat