Senior Data Engineer

RESPONSIBILITIES:

• Design, build, and maintain scalable data pipelines and architectures to support analytical and operational workloads.
• Develop and optimize ETL/ELT pipelines, ensuring efficient data extraction, transformation, and loading from various sources.
• Work closely with backend and platform engineers to integrate data pipelines into cloud-native applications.
• Manage and optimize cloud data warehouses, primarily BigQuery, ensuring performance, scalability, and cost efficiency.
• Implement data governance, security, and privacy best practices, ensuring compliance with company policies and regulations.
• Collaborate with analytics teams to define data models and enable self-service reporting and BI capabilities.
• Develop and maintain data documentation, including data dictionaries, lineage tracking, and metadata management.
• Monitor, troubleshoot, and optimize data pipelines, ensuring high availability and reliability.
• Stay up to date with emerging data engineering technologies and best practices, continuously improving our data infrastructure.

REQUIREMENTS:

• Certified SnowPro.
• Experience collaborating with distributed teams across North America and Latin America.
• 5+ years of experience in data engineering, building modern cloud-based data platforms.
• Strong hands-on experience with Snowflake, including performance tuning, security, and data modeling.
• Advanced SQL skills for analytics engineering and data transformation.
• Proficiency in Python for data processing, automation, and orchestration.
• Experience with dbt or similar analytics engineering frameworks.
• Familiarity with orchestration tools such as Dagster or Apache Airflow.
• Experience working with clickstream and event data - ingestion, modeling, and real-time or near-real-time processing at scale.
• Experience enabling or supporting machine learning, feature engineering, or AI-driven use cases on top of data platforms.
• GCP certified (Associate Cloud Engineer or Professional Data Engineer).
• Solid understanding of data privacy, governance, and compliance best practices.
• Strong problem-solving skills and a pragmatic, delivery-oriented mindset.
• Strong problem-solving skills, with the ability to debug and optimize complex data workflows.
• Excellent English communication and collaboration skills.

NICE TO HAVES:

• Experience with Snowflake Cortex, Snowpark, or ML workflows integrated with Snowflake.
• Familiarity with GenAI or LLM-enabled analytics use cases (e.g., semantic layers, AI-assisted insights, decisioning).
• Experience with Databricks or hybrid Snowflake + Databricks architectures.
• Exposure to real-time or near-real-time data pipelines.
• Experience with BI tools (e.g., Looker, Tableau, Power BI).
• Infrastructure as Code experience (e.g., Terraform) in data environments.
• Familiarity with CDPs, marketing platforms, and digital experience ecosystems (e.g., Segment, Contentful, personalization tools).