Senior Data Engineer
- Role
- Data Engineering
- Experience
- Senior
- Company size
- Mid-size
Open to Anywhere in LATAM. Set where you work from to check your eligibility.
No BS summary
Senior Data Engineer with 7+ years in data engineering and deep Snowflake expertise. Must know SQL, ELT/ETL pipeline patterns, data modeling approaches, and at least one cloud platform: AWS, Azure, or GCP. Role is for Costa Rica / LATAM.
Core skills
Required skills
Optional skills
BlueCloud is a Snowflake Elite Partner and the 2026 CoCo Catalyst Snowflake Partner of the Year. We help enterprise organizations move from fragmented legacy systems to unified, AI-ready Snowflake platforms — delivering data migration, engineering, governance, BI & analytics, and AI/ML solutions 40–50% faster than traditional approaches. With 450+ Snowflake consultants, 200+ enterprise transformations under our belt, and a 100% Snowflake focus, we combine advisory-led thinking with AI-powered accelerators to turn months of work into weeks of results. Our clients span Financial Services, Healthcare & Life Sciences, Retail, Manufacturing, Energy, and more — and the outcomes speak for themselves: 97% faster reports, 40% fraud reduction, $1.5M in client savings, and 10× client growth. We don't just strategize — we execute.
Senior Data Engineer This is a senior-level role focused on the design, development, and ownership of data solutions built primarily on Snowflake Data Cloud. You will lead the architecture and implementation of scalable data pipelines, establish robust data models, and enforce data governance and security standards across the platform. Key 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. Requirements 7+ 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. Nice to Have 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.
What you'll do
- 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.
- 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.
- 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.
What they require
- 7+ 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.
- Preferred: Exposure to data governance frameworks and security best practices within cloud environments.
- Preferred: Experience working in a consultancy or multi-client environment.
- Experienced in building lasting relationships.
- Passionate about making meaningful contributions to the team.
BlueCloud is a leading AI and data transformation consultancy focused exclusively on helping enterprises unlock the value of their data. As a Snowflake Elite Partner, BlueCloud combines deep advisory expertise, enterprise-scale data modernization capabilities, and proprietary AI accelerators to help organizations move from strategy to measurable business outcomes faster than traditional consulting models.