Role Description 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. Qualifications - Bachelor’s degree in Computer Science, Information Technology, Data Engineering, or a related field (or equivalent professional experience). - Proven experience developing end-to-end data pipelines extracting/transforming/loading data from REST APIs, relational databases, cloud storage, and flat files. - Demonstrated hands-on experience with Snowflake (virtual warehouses, streams, tasks, stages, Snowpipe, secure data sharing, and performance optimization). - Advanced SQL development skills with the ability to write complex queries, tune performance, and optimize large-scale workloads. - 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). - 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. Requirements - Certifications: SnowPro, Azure Data Engineer Associate, or equivalent cloud data platform certifications (preferred). - Experience with big data technologies, machine learning, data science platforms, or advanced analytics (preferred). - Familiarity with BI tools such as Power BI, Tableau, or similar visualization platforms (preferred). - Experience with Agile delivery frameworks and DevOps practices (preferred). 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. - 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. - 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. - 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. - 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). - 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. Benefits - Competitive salary and bonuses, including performance-based salary increases. - Generous paid-time-off policy. - Flexible working hours. - Work remotely. - Continuing education, training, conferences. - Company-sponsored coursework, exams, and certifications.