Data Engineer-Senior Software Engineer

About the Role

This role is ideal for engineers passionate about cloud data engineering and applied AI who want to build production-grade systems that create real business impact for iconic global brands.

What You'll Do

• Design, develop, and maintain GCP-based data pipelines integrating multiple business applications and data sources.

• Build and deploy AI/ML models and data products using GCP AI services (Vertex AI, BigQuery ML, Gemini APIs).

• Develop data transformation logic using PySpark, SQL, and Python on GCP platforms (Dataflow, Dataproc, BigQuery).

• Work within a DevOps environment with CI/CD pipelines, automated deployments, and cloud-native monitoring.

• Participate in code reviews, uphold coding standards, and ensure data quality and pipeline reliability.

• Perform root cause analysis on data issues and implement robust, long-term solutions.

• Support business stakeholders with data requirements, analytics insights, and reporting needs.

• Contribute to improving automation, testing, and observability practices across the data platform.

Who You Are

• 4-7 years of overall experience, with at least 3+ years in a Data Engineering or Cloud AI role.

• Graduate degree in Computer Science, Engineering, or equivalent.

• Mandatory: Hands-on expertise with GCP data and AI services:

• BigQuery - data modeling, optimization, partitioning, and clustering

• Vertex AI - model training, deployment, and MLOps pipelines

• Cloud Dataflow / Dataproc - batch and streaming data processing

• Cloud Composer (Apache Airflow) - pipeline orchestration

• Cloud Storage, Pub/Sub, and Bigtable - data storage and real-time streaming

• Mandatory: Experience building and operationalizing AI/ML models in GCP (Vertex AI, BigQuery ML, or Generative AI APIs).

• Proficiency in Python and SQL for data engineering and AI/ML workflows.

• Familiarity with PySpark for large-scale data transformations.

• Strong understanding of data pipeline architecture - batch, micro-batch, and streaming patterns.

• Experience with version control and CI/CD tools (GitHub, Cloud Build, Jenkins).

• Proficiency in Linux shell scripting and automation.

Good-to-Have Skills

• Experience with LLM integration or Generative AI on GCP (Gemini APIs, Model Garden, or similar).

• Familiarity with data governance, data cataloging (Dataplex), and data lineage on GCP.

• Exposure to dbt (data build tool) for transformation and documentation.

• Knowledge of enterprise integration patterns and event-driven architectures.

• Experience with BI and reporting tools such as Looker, Power BI.

• Strong communication and stakeholder collaboration skills in cross-functional, global teams.