This is a fully remote position, open to applicants in Peru.

• Engage in cross-functional meetings to establish project goals and scope.

• Assess and prioritize business needs pertaining to data.

• Design and implement data extraction, transformation, and loading pipelines (ETL/ELT).

• Create applications for retrieving data from diverse sources and formats (JSON, XML, PDF, etc.).

• Produce clean, efficient, and scalable code while adapting to new technologies as required.

• Apply data quality practices throughout the ingestion and transformation stages.

• Enhance services, queries, and processes to minimize operational costs and boost performance.

• Ensure the functionality, integrity, and security of data engineering processes.

• Bachelor’s degree in Computer Systems Engineering, Computer Science, or a related discipline.

• Specialization in Data Engineering is preferred.

• 5 to 8 years of experience in comparable roles.

• Practical experience with batch and streaming data processing.

• Intermediate to advanced proficiency in English.

• Proficiency in programming languages: Java, Scala, Python, and SQL.

• Experience with data processing frameworks such as Spark and Flink.

• Familiarity with SQL and NoSQL databases including PostgreSQL, Cassandra, and MongoDB.

• Experience with orchestration and ETL tools like Airflow, Airbyte, and Stitch.

• Proven track record of managing large-scale data transformations across various formats.

• Design and architecture experience with Data Lakes, Data Warehouses, and Lakehouse solutions.

• Expertise in data modeling (star schema, snowflake schema, OBT).

• Development and integration of REST APIs.

• Knowledge of Agile methodologies and version control using Git.

• Experience with web scraping projects is a plus.

• Familiarity with additional programming languages such as Go or JavaScript is advantageous.

• Experience with streaming and messaging systems like Kafka and RabbitMQ is a bonus.

• Background in data science projects is considered a plus.

• Competitive salary and performance-based bonuses.

• Opportunities for professional growth and development.

• Flexible work arrangements and a supportive work environment.

• Comprehensive health and wellness programs.

• Access to the latest tools and technologies in the field.

Data Engineer

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