Data Engineer en VieMed

Essential Duties and Responsibilities:

• Engineering & Development

• Build and maintain scalable ETL/ELT pipelines for batch and streaming data.
• Write high-quality SQL and Python for data transformations and integrations.
• Optimize data models, queries, and workflows for performance and cost efficiency.
• Partner with analysts and data scientists to deliver reliable datasets for BI, analytics, and ML.

• Architecture & Infrastructure

• Contribute to the design of modern data warehouse and lakehouse solutions (Snowflake, Redshift, BigQuery, Databricks, etc.).
• Implement data orchestration and transformation frameworks (Airflow, dbt, Prefect).
• Support data infrastructure in the cloud (AWS/GCP/Azure), ensuring scalability, reliability, and security.

• Mentorship & Collaboration

• Provide technical guidance and informal mentoring to less experienced data engineers.
• Participate in code reviews, design discussions, and knowledge-sharing sessions.
• Promote best practices in coding standards, documentation, and testing.

• Quality & Operations

• Establish and maintain standards for data quality, observability, and reliability.
• Troubleshoot pipeline and infrastructure issues in production environments.
• Contribute to automation and monitoring efforts to reduce manual operations.

Minimum Qualifications:

• Experience

• 4–6+ years of experience in data engineering or related fields.
• Prior experience collaborating with and mentoring junior engineers.

• Technical Skills

• Advanced SQL and query optimization.
• Strong Python for data engineering (Pandas, PySpark, or similar).
• Hands-on experience with data orchestration (Airflow, dbt, Prefect).
• Familiarity with modern cloud-based data platforms (AWS Redshift, Snowflake, BigQuery, Synapse, Databricks).
• Strong understanding of data modeling and schema design.

Preferred Knowledge, Skills and Abilities:

• Experience with streaming technologies (Kafka, Kinesis, Pub/Sub).
• Familiarity with CI/CD and version control workflows.
• Exposure to data governance and security frameworks.

You will be expected to work during normal business hours, which are Monday through Friday, 8:00 a.m. – 5:00 p.m. Please note this job description is not designed to cover and/or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee for this job. Duties and responsibilities may change at any time with or without notice.