What are the responsibilities and job description for the Data Architect with Python and GCP cloud - Full Time Role position at Saransh Inc?
Role: Senior Data Architect
Location: Issaquah, WA (Day 1 Onsite)
Job Type: Full-Time
Must Have Skills
Data Pipeline, C#, Python, Google Cloud Platform (GCP), Data Quality
Job Description
Looking for a Data Architect who will play a role in designing, developing, and implementing data pipelines and data integration solutions using Python and Google Cloud Platform services.
Responsibilities
Location: Issaquah, WA (Day 1 Onsite)
Job Type: Full-Time
Must Have Skills
Data Pipeline, C#, Python, Google Cloud Platform (GCP), Data Quality
Job Description
Looking for a Data Architect who will play a role in designing, developing, and implementing data pipelines and data integration solutions using Python and Google Cloud Platform services.
Responsibilities
- Develop, construct, test and maintain data acquisition pipelines for large volumes of structured and unstructured data. This includes batch and real-time processing
- Develop and maintain data pipelines and ETL processes using Python.
- Design, build, and optimize data models and data architecture for efficient data processing and storage
- Implement data integration and data transformation workflows to ensure data quality and consistency
- Working experience as a Data Engineer
- Experienced in migrating large-scale applications from legacy systems to modern architectures.
- Good programming skills in Python and experience with Spark for data processing and analytics
- Experience in Google Cloud Platform services such as GCS, Dataflow, Cloud Functions, Cloud Composer, Cloud Scheduler, Datastream (CDC), Pub/Sub, BigQuery, Dataproc, etc. with Apache Beam (Batch & Stream data processing).
- Develop JSON messaging structure for integrating with various application
- Leverage DevOps and CI/CD practices (GitHub, Terraform) to ensure the reliability and scalability of data pipelines.
- Experience with scripting languages like Shell, Perl etc.
- Design and build an ingestion pipeline using Rest API.
- Experience with data modeling, data integration, and ETL processes
- Strong knowledge of SQL and database systems
- Familiarity with managing cloud-native databases.
- Understanding of security integration in CI/CD pipelines.
- Understanding of data warehousing concepts and best practices
- Proficiency in working with large-scale data sets and distributed computing frameworks
