Analytics Engineer creating data products that meet various business needs for the fintech company Stone. Responsible for data pipelines, monitoring, and ensuring data quality.
About the role
- Analytics Engineer at Becklar focusing on data engineering and analytics for life-saving solutions. Building scalable data pipelines and collaborating with stakeholders to support data-driven decisions.
Responsibilities
- Design, develop, and maintain scalable data pipelines using modern Big Data tools (Fivetran, Snowflake, Sigma)
- Transform complex, raw datasets into clean, curated data models (e.g., dimensional models, star/snowflake schemas).
- Write efficient SQL and reusable data transformation logic using tools like dbt.
- Collaborate with analysts, data scientists, and stakeholders to define and deliver data solutions.
- Ensure data quality, accuracy, and timeliness across the data platform.
- Optimize queries and system performance in large-scale environments.
- Work with cloud infrastructure (AWS, GCP, or Azure) to manage data storage and compute resources.
- Enforce best practices in data governance, version control, and documentation.
- Monitor and troubleshoot data workflows, ensuring SLAs are met.
Requirements
- Bachelors or Masters in Computer Science, Information Systems, Data Science, or a related field.
- 3+ years of experience in data engineering or analytics engineering roles.
- Proficiency in SQL and large-scale data modeling.
- Experience with Big Data tools
- Hands-on experience with ELT/ETL and orchestration tools
- Familiarity with cloud data ecosystems (AWS, GCP, or Azure).
- Strong understanding of data warehousing and analytics processing.
- Experience with containerization and CI/CD (e.g., DevOps pipelines, GitHub Actions) preferred.
- Knowledge of data governance, privacy, and compliance preferred.
- Familiarity with BI tools (Sigma preferred).
Benefits
- flexibility in a hybrid work model
- data-driven, innovation-focused company culture
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
Design and optimize scalable data pipelines and models for terabyte - scale datasets. Collaborate with stakeholders to ensure data quality, governance, and actionable analytics.
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