Data Engineer – Build Scalable Pipelines & Analytics

About the role

This position enables data‑driven decision making by designing, building, and maintaining reliable data pipelines. You will work with a modern data stack, collaborate closely with business stakeholders, and apply AI‑assisted development tools to accelerate delivery.

Key responsibilities

• Design, develop, and operate scalable ETL pipelines supporting business analytics.
• Perform data manipulation, transformation, and cleansing to ensure high data quality.
• Develop and maintain Snowflake databases and optimized data models.
• Leverage AWS services for storage, processing, and analytics workloads.
• Manage cloud infrastructure as code using Terraform.
• Orchestrate workflows and schedule jobs with Apache Airflow.
• Build modular data transformations with dbt, including testing and documentation.
• Create and maintain Looker reports and dashboards.
• Apply AI and machine learning concepts to improve data workflows and automation.
• Use AI coding assistants (e.g., Claude Code, GitHub Copilot) daily to boost productivity.

Required profile

• Strong Python programming skills for data engineering tasks.
• Proficiency in SQL for database management and querying.
• Hands‑on production experience with Apache Airflow and dbt.
• Experience automating infrastructure with Terraform.
• Solid background using AWS services for data workloads.
• Deep knowledge of Snowflake, including administration.
• Experience building Looker dashboards and reports.
• Comfortable using AI coding tools in daily development.
• Excellent English communication and a collaborative mindset.

Required skills

• Python
• SQL
• Apache Airflow
• dbt (Data Build Tool)
• Terraform
• AWS (e.g., S3, Redshift, Glue)
• Snowflake
• Looker
• AI coding assistants (Claude Code, GitHub Copilot)