Mid-Level Data Engineer

At Nava, we believe in the power of technology to transform businesses — and we have a challenging and strategic opportunity waiting for you.

Come write code with us! 🚀

We are looking for a Mid-Level Data Engineer to build, evolve, and monitor data platforms and pipelines in a cloud environment. We are looking for a professional with experience in data engineering, focused on performance, scalability, and data quality, along with a collaborative profile to work on strategic data and analytics projects.

Key Responsibilities

• Develop, maintain, and optimize data pipelines in cloud environments, ensuring performance, scalability, and reliability.
• Build and maintain solutions for data ingestion, transformation, and delivery.
• Develop routines and processes using Databricks and AWS services.
• Monitor environments and data pipelines, performing performance analysis, troubleshooting, and continuous improvements.
• Implement and maintain best practices for observability, including monitoring, logs, metrics, and alerts.
• Create and maintain reusable components, templates, and frameworks to standardize data engineering processes.
• Support automation initiatives, code versioning, and CI/CD practices.
• Collaborate with business, analytics, and technology teams to meet the company's data needs.
• Ensure the application of best practices related to data governance, security, and quality.

Requirements and Skills

• Experience as a Data Engineer or in related roles.
• Knowledge of cloud data platforms, preferably AWS.
• Experience with AWS services such as S3, Glue, Lambda, and Redshift.
• Hands-on experience with Databricks for developing and maintaining notebooks and jobs.
• Knowledge of data processing and transformation.
• Experience with advanced SQL and Python.
• Knowledge of code versioning using Git.
• Experience with monitoring and observability practices for data pipelines.
• Knowledge of data modeling, partitioning, and processing optimization.
• Familiarity with agile methodologies and collaborative work in cross-functional teams.

Preferred Qualifications

• AWS and/or Databricks certifications.
• Experience in Big Data environments and handling large data volumes.
• Knowledge of Apache Airflow, dbt, Apache Spark, or similar tools.
• Experience with DataOps and DevOps practices.
• Experience with Infrastructure as Code (IaC).
• Knowledge of data governance and information security.
• Experience implementing frameworks and accelerators for data engineering.
• Experience in cloud data platform modernization projects.

Interested? Apply for the position and take your technical interview with SophIA:

https://entrevista.starmindai.ai

Code: NAVA-BMGDADOS