BlueCloud Services, Inc. - Senior Snowflake Data Engineer
Requirements
• 7+ years of experience in data engineering, including significant hands-on experience with Snowflake. • Advanced SQL skills, including complex transformations, query optimization, and stored procedure development. • Strong Python development experience for data processing, automation, and pipeline development. • Hands-on experience with Snowpark and Snowflake-native capabilities such as Dynamic Tables, Streams, and Tasks. • Proven experience designing and supporting scalable ELT/ETL pipelines in production environments. • Strong understanding of Snowflake performance and cost optimization, including warehouse sizing, query profiling, clustering, and workload management. • Experience with data modeling, incremental processing, pipeline orchestration, and dependency management. • Experience with dbt or a comparable data transformation framework. • Familiarity with at least one major cloud platform: AWS, Azure, or GCP. • Experience with Git, CI/CD, automated testing, and modern software delivery practices. • Strong troubleshooting, analytical, and problem-solving skills. • Effective written and verbal communication skills, including the ability to collaborate directly with technical and business stakeholders. • Experience with Fivetran, Kafka, Airflow, or similar ingestion and orchestration tools. • Familiarity with Terraform or another infrastructure-as-code platform. • Experience with Snowflake Iceberg Tables or modern lakehouse architectures. • Exposure to Snowflake Cortex, including Cortex Analyst, Cortex Search, or Cortex LLM functions. • Experience supporting business continuity and disaster recovery strategies. • SnowPro Core or SnowPro Advanced certification. • We are looking for someone who is experienced in building lasting relationships and is passionate about making meaningful contributions to our team. Don't be mistaken, this is a challenging career path but also highly rewarding. Are you up for the challenge? If so, stop reading and start applying. • We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
Responsibilities
• Design, develop, and maintain scalable data pipelines and transformation workflows within Snowflake. • Build and optimize ELT/ETL processes using SQL, Python, Snowpark, dbt, and Snowflake-native capabilities. • Modernize existing Python- and stored-procedure-based pipelines using set-based processing, incremental loading, and reusable engineering patterns. • Implement Snowflake-native data-processing solutions using Dynamic Tables, Streams, Tasks, and stored procedures. • Improve platform performance and cost efficiency through query tuning, warehouse right-sizing, clustering strategies, workload isolation, and auto-suspend and auto-resume policies. • Develop reliable orchestration, dependency management, monitoring, error handling, retry, and recovery mechanisms. • Design and maintain dimensional, relational, and domain-oriented data models. • Implement data-quality checks, observability, testing, lineage, and documentation standards. • Integrate data from batch and real-time sources using tools such as Fivetran, Kafka, Airflow, or similar technologies. • Contribute to CI/CD pipelines, infrastructure-as-code practices, and automated deployment processes. • Work closely with architects and client stakeholders to translate business and technical requirements into production-ready solutions. • Participate in code reviews, technical design discussions, estimation, and Agile delivery activities.
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