Job Description

About the Role

This role supports data-driven decision making by building reliable, scalable data pipelines and enabling analytics across the organization. You'll work with modern data stack tools to ensure strong engineering practices that support accuracy, reliability, and growth while collaborating closely with business stakeholders.

What You'll Do

• Design, build, and maintain scalable data pipelines and ETL processes to support business analytics

• Perform data manipulation, transformation, and cleansing to ensure accuracy and integrity

• Develop and maintain database solutions using SQL

• Implement and optimize data models and storage solutions in Snowflake

• Leverage AWS services for data storage, processing, and analytics

• Use Terraform to manage and deploy cloud resources as infrastructure-as-code

• Orchestrate workflows and schedule pipelines using Apache Airflow

• Work with dbt (Data Build Tool) to develop, test, and maintain modular data transformations

• Create and maintain reports and dashboards in Looker

• Apply AI and machine learning concepts to improve data workflows, automation, and insights generation

• Use AI coding tools actively in daily development workflow to accelerate delivery

• Collaborate with the team to continuously improve data engineering practices and processes

How You'll Succeed

• You deliver reliable, well-tested pipelines that scale with business growth

• You proactively identify data quality issues and implement solutions before they impact stakeholders

• You communicate technical concepts clearly and confidently in collaborative settings

• You balance speed with quality, knowing when to optimize and when to ship

• You share knowledge openly and help elevate team capabilities

Who You Are

• Strong Python programming skills for data engineering tasks

• Proficiency in data manipulation and transformation

• Strong SQL skills for database management and querying

• Hands-on production experience with Apache Airflow for workflow orchestration

• Hands-on production experience with dbt for building scalable and maintainable data models

• Proficiency with Terraform for infrastructure automation

• Experience with AWS services for data engineering workloads

• Proficiency in Snowflake including administration experience

• Experience with Looker for reporting and dashboards

• Active daily use of AI coding tools (Claude Code, GitHub Copilot, or similar) in development workflow

• Exposure to AI concepts or tools applied to data workflows or analytics use cases

• Strong understanding of data modeling principles and best practices

• Excellent English communication skills. vocal, extroverted, and confident sharing ideas in collaborative settings