Data Engineer
First seen by Alion on Sep 17, 2026.
Job Description :
We are looking for a Data Engineer to design, build, and maintain scalable data pipelines and cloud-based data platforms on Google Cloud Platform. You will work with engineering, analytics, and business teams to ensure data is reliable, accessible, and optimized for downstream use cases.
Key Responsibilities :
- Design, develop, and maintain scalable data pipelines on Google Cloud Platform (GCP).
- Build and manage batch and real-time data processing workflows.
- Develop data ingestion, transformation, and integration solutions across multiple data sources.
- Work with BigQuery to design data models, optimize queries, and improve data warehouse performance.
- Build ETL/ELT pipelines using services such as Dataflow, Dataproc, Cloud Composer, and Pub/Sub.
- Manage and process data stored in Google Cloud Storage.
- Ensure data quality, consistency, security, and reliability across data platforms.
- Monitor and troubleshoot data pipelines and production workflows.
- Optimize cloud infrastructure and data processing workloads for performance and cost.
- Collaborate with data scientists, analysts, software engineers, and business stakeholders.
- Implement CI/CD and automation practices for data engineering workflows.
- Maintain technical documentation for data pipelines, architecture, and processes.
Required Skills :
- Strong hands-on experience with Google Cloud Platform.
- Experience with BigQuery, Cloud Storage, Dataflow, Dataproc, Pub/Sub, and Cloud Composer.
- Strong programming skills in Python.
- Strong proficiency in SQL.
- Experience designing and building ETL/ELT pipelines.
- Good understanding of data warehousing, data modeling, and distributed data processing.
- Experience working with large-scale structured and unstructured datasets.
- Knowledge of Apache Beam, Spark, or similar data processing frameworks.
- Familiarity with Git and version control.
- Strong problem-solving and debugging skills.
Good to Have :
- Experience with Apache Airflow.
- Knowledge of Terraform or Infrastructure as Code.
- Experience with Docker and Kubernetes.
- Familiarity with Kafka or other streaming technologies.
- Exposure to dbt.
- Experience implementing data governance and data security practices.
- Knowledge of GCP IAM, networking, and cloud security.
- Google Cloud certification such as Professional Data Engineer.
Skills
Data Engineering, Google Cloud Platform, Data Modeling, BigQuery, Data Ingestion, Data Integration, ETL, Data Pipeline, Python, SQL, Data Warehousing