Senior Data Engineer
New
N
NortalDigital Transformation
Latin AmericaFull-TimeSenior
Salary not disclosed
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Job Details
- Languages
- English
- Required Skills
- PythonSQLCloud ComputingSparkCI/CDData modelingDatabricks
Requirements
- Bachelor's Degree in Computer Science, Engineering, or a related field.
- Strong experience building and operating data pipelines using SQL and Python in cloud environments.
- Deep expertise in SQL, including query optimization and performance tuning on large datasets.
- Hands-on experience with Databricks, Apache Spark, or similar distributed processing frameworks.
- Solid understanding of modern data architecture patterns, including Lakehouse, ELT, and layered data models.
- Proven experience designing scalable data models for analytics.
- Expertise in monitoring, debugging, and maintaining production data systems.
- Experience working closely with business stakeholders to translate ambiguous requirements into technical solutions.
- Familiarity with CI/CD pipelines and version-controlled data workflows.
- Advanced English Level.
Responsibilities
- Design, build, and maintain scalable data pipelines end-to-end (ingestion, transformation, and serving layers).
- Translate business KPIs and analytical requirements into production-ready datasets for analytics and AI use cases.
- Develop and optimize data models using modern approaches such as Bronze/Silver/Gold layered architecture.
- Own and evolve key components of a Lakehouse platform based on technologies like Databricks and Spark.
- Build and maintain high-quality, production-grade datasets to support analytics, reporting, and machine learning.
- Establish and enforce data engineering standards, reusable frameworks, and best practices across teams.
- Ensure data quality and reliability through validation, monitoring, alerting, and SLA management.
- Productionize and scale analytical prototypes into robust, maintainable data pipelines.
- Collaborate with cross-functional teams to support product analytics, experimentation, and user behavior tracking.
- Improve pipeline performance and optimize query efficiency at scale.
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