BlueCloud Services, Inc. - #5 Senior Data Engineer- Costa Rica, LATAM
Requirements
• 5+ years of hands-on experience in data engineering, with a strong professional track record in place of formal credentials. • Proven, deep expertise with Snowflake- including performance optimisation, cost management, security features, and data architecture. • Solid working knowledge of SQL and at least one scripting language, preferably Python. • Experience designing and building ELT/ETL pipelines across batch, incremental, and CDC patterns. • Familiarity with data modeling approaches such as Dimensional Modeling, Data Vault, or Lakehouse. • Experience with at least one cloud platform (AWS, Azure, or GCP) in a data engineering context. • Hands-on experience with dbt, Airflow, or dbt Cloud. • Exposure to data governance frameworks and security best practices within cloud environments. • Experience working in a consultancy or multi-client environment. • 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
• Data Pipeline & Engineering • Design, build, and own scalable data pipelines and ingestion processes using SQL, Python, dbt, and cloud-native tools. • Architect and implement ELT/ETL patterns across batch, incremental, and CDC pipelines. • Lead the development of data models using Dimensional Modeling, Data Vault, or Lakehouse approaches. • Define and implement data transformation logic, data quality validations, and business rules. • Platform & Cloud Engineering • Own the design and optimization of Snowflake environments, including warehouse sizing, cost governance, storage standards, schema management, and performance tuning. • Work with cloud platforms (AWS, Azure, or GCP) to integrate with Snowflake and deliver high-performance, cost-efficient solutions. • Lead pipeline orchestration using Airflow, dbt Cloud, or similar tools. • Governance & Security • Establish and enforce data governance frameworks, access controls, and security protocols- with particular focus on Snowflake-native capabilities such as row-level security, dynamic data masking, and data sharing. • Define and maintain data quality standards, lineage documentation, and compliance requirements.
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