Data Engineer

• Build and migrate existing data solutions to Google Cloud Platform (GCP) to support data analytics and ML/AI products.
• Develop new data products on GCP using DBT and BigQuery.
• Collaborate with Solution Architects and Business Experts to design and implement relevant and scalable data models.
• Integrate and synchronize data from multiple sources using Cloud Functions and Python.
• Build and maintain end-to-end data pipeline components using Terraform, Cloud Workflows, and other GCP services., * A collaborative, technology-driven environment focused on innovation and continuous improvement.
• Opportunities to work with modern cloud architectures and advanced analytics solutions.
• A dynamic team culture where your ideas and expertise contribute directly to impactful data products.
• A platform to grow your cloud engineering and ML/AI data capabilities.

• 6-8 years of overall experience, including hands-on work as a Data Engineer on cloud-based data platforms or in advanced analytics environments.
• Strong expertise in GCP services including BigQuery, Cloud Run, Cloud Functions, Pub/Sub, Cloud Composer, etc.
• Proficiency in SQL, DBT, Python, and infrastructure-as-code tools like Terraform.
• Experience with CI/CD pipelines and version control.
• Knowledge of PowerBI or similar reporting tools.
• Experience working with various data formats such as Avro and Parquet.
• Familiarity with both NoSQL and RDBMS databases.
• Programming experience in a data-centric context using Python, Java, or Scala.

You should possess the ability to:

• Design, deploy, and maintain scalable cloud-native data pipelines on GCP.
• Analyze complex business and technical requirements and translate them into robust data solutions.
• Optimize data flows for performance, reliability, and cost efficiency.
• Work collaboratively across multidisciplinary engineering and analytics teams.
• Troubleshoot issues across data ingestion, transformation, and workflow orchestration layers.