Posted on: 11/08/2025
About the Role :
We are seeking a skilled and versatile Full Stack Data Engineer with strong expertise in Python and cloud-based data engineering tools to design, develop, and maintain end-to-end data pipelines and infrastructure on Google Cloud Platform (GCP). The ideal candidate will have hands-on experience with modern data orchestration, transformation, and storage technologies, enabling scalable and reliable data solutions that support analytics and business intelligence.
Key Responsibilities :
- Design, develop, and maintain scalable data pipelines using Python, PySpark, and Apache Airflow for data ingestion, transformation, and processing.
- Build and manage data workflows with orchestration tools such as Airflow and Tekton to automate data movement and processing.
- Develop and deploy data transformation scripts using DBT (Data Build Tool) and DataForm.
- Work with Google Cloud Platform services including Dataproc, Cloud Storage, BigQuery, Pub/Sub, and Data Fusion to create integrated data solutions.
- Implement infrastructure as code using Terraform to provision and manage cloud resources efficiently.
- Design and develop RESTful APIs to facilitate data access and integration across systems.
- Collaborate with data scientists, analysts, and product teams to understand data requirements and deliver high-quality datasets.
- Optimize data models and queries for performance and cost efficiency in BigQuery and other data stores.
- Implement monitoring, alerting, and logging to ensure reliability and troubleshoot issues in data pipelines.
- Adhere to data governance, security best practices, and compliance requirements.
- Document data architectures, processes, and standards to maintain knowledge sharing and consistency.
Required Skills and Qualifications
- Bachelors degree in Computer Science, Engineering, or a related field.
- Proven experience in data engineering with strong Python programming skills.
- Hands-on experience with Apache Airflow for workflow orchestration and automation.
- Proficiency in PySpark and working with big data processing frameworks.
- Experience with Google Cloud Platform services : Dataproc, Cloud Storage, BigQuery, Pub/Sub, Data Fusion.
- Familiarity with infrastructure as code using Terraform.
- Experience with data transformation tools such as DBT and DataForm.
- Strong understanding of data modeling, ETL/ELT processes, and data warehousing concepts.
- Ability to develop and consume RESTful APIs.
- Knowledge of containerization and CI/CD pipelines is a plus.
- Excellent problem-solving skills and attention to detail.
- Strong communication and collaboration skills.
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Posted in
Data Engineering
Functional Area
Data Engineering
Job Code
1528331
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