Data Engineer – Google Cloud Platform (GCP), BigQuery, Python & Data Pipelines
Location: Hybrid – 3 Days per Week On-Site
Job Summary
Skilled Data Engineer with hands‑on Google Cloud Platform (GCP) experience to design, build, and maintain scalable data pipelines and cloud‑based data solutions. Expertise in data warehousing, ETL/ELT development, big data technologies, and GCP services to support enterprise analytics and business intelligence initiatives.
Key Responsibilities
- Design, develop, and maintain scalable batch and real‑time data pipelines on GCP
- Build and optimize data ingestion frameworks from multiple structured and unstructured data sources
- Develop ETL/ELT processes using GCP‑native services and modern data engineering tools
- Design and implement data models for analytics, reporting, and machine learning use cases
- Manage and optimize data storage solutions using BigQuery and Cloud Storage
- Monitor data quality, performance, security, and governance standards
- Collaborate with business stakeholders, data analysts, architects, and data scientists to deliver enterprise data solutions
- Implement CI/CD, automation, and DevOps practices for data engineering workloads
- Troubleshoot data processing issues and optimize pipeline performance
- Ensure compliance with data security and privacy requirements
Required Skills
- Strong experience in Data Engineering and data pipeline development
- Hands‑on experience with Google Cloud Platform (GCP) services including:
- BigQuery
- Cloud Storage
- Dataflow
- Pub/Sub
- Dataproc
- Cloud Composer (Airflow)
- Cloud Functions
- Cloud Run
- Strong programming skills in:
- Python
- SQL
- PySpark
- Experience with ETL/ELT frameworks and data integration tools
- Strong knowledge of data warehousing concepts and dimensional modeling
- Experience working with relational and NoSQL databases
- Knowledge of real‑time and streaming data architectures
- Understanding of CI/CD pipelines, GitHub, and DevOps practices
- Experience with data quality, metadata management, and governance
Preferred Skills
- Experience with Apache Spark, Hadoop, Kafka, and Airflow
- Exposure to machine learning data pipelines and MLOps
- Experience with Terraform or Infrastructure as Code (IaC)
- Knowledge of containerization technologies such as Docker and Kubernetes
- Experience in Banking, Financial Services, Insurance, or large enterprise environments
Required Qualifications
- Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, or a related field
- Excellent analytical and problem‑solving skills
- Strong communication and stakeholder management skills
- Experience working in Agile/Scrum environments
Essential Skills
- Google Cloud Platform (GCP)
- BigQuery
- Python
- SQL
- PySpark
- ETL/ELT
- Dataflow
- Cloud Composer (Airflow)
- Cloud Storage
- CI/CD
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