Design, develop, and implement scalable and efficient data pipelines using GCP services (e.g., Dataflow, Cloud Functions, Workflows) for ETL/ELT processes.
Build robust and scalable solutions for orchestrating data workflows, ensuring data integrity.
Develop and optimize data models and data warehouse solutions in BigQuery.
Write complex and highly optimized SQL queries to extract, transform, and load data.
Define and enforce best practices for data platform development and usage.
Evaluate new technologies to improve our data capabilities.
Provide technical expertise and guidance to junior team members.
Collaborate closely with team members to understand data requirements and propose solutions.

Strong proficiency in Python and SQL, including advanced SQL query writing and optimization.
Java is also good to have.
Experience with Google Cloud Platform (GCP) services, such as BigQuery, Cloud Run, Data Catalog, Cloud Functions, IAM, GCS, Monitoring, Workflows, Cloud SQL, and Secret Manager.
Solid understanding of backend development concepts, including CI/CD pipelines (CircleCI), Docker, and microservices architecture.
Knowledge of data modeling, data architecture, data pipelines, ETL/ELT processes, and business intelligence tools.
Familiarity with business intelligence tools, with experience building dashboards in Sisense being a significant advantage.
Exp. in shell scripting.
AWS is good to have.
Excellent communication and interpersonal skills to effectively collaborate with team members and stakeholders.
Strong problem-solving and analytical abilities to identify and resolve complex technical challenges.
Ability to work independently and manage tasks effectively.
A strong passion for data and a commitment to delivering high-quality data solutions.
Experience with data mesh principles and practices would be a significant advantage.
Familiarity with data governance and compliance frameworks is desirable.

Data Engineer I

Key skills