Job Location: Poona
GCP- Data Architect – (0091991)
Description
Mandatory Skills:
Candidate should have 12-16 years of experience in GCP Data Architect with BigQuery + Teradata and ELT – Data Build Too –(DBT) / (Informatica) Development and Design & Development experience:
Job description for GCP Data Architect:
Primary Technical skills:
Roles and Responsibilities
Experience in data engineering or architecture with an emphasis on data analytics and reporting
Developing thought leadership materials and being recognized in the Information Technology industry as a credible participant in the digital and cloud dialogue
Experience in roles conducting requirements gathering, writing user stories and creating design
Experience in using GCP services to analyze data, build data models and generate visualizations
Excellent communication skills with the ability to influence client business and IT teams
Ability to guide and drive the technical discussions with IT., Business and Data modelers and Architects
Experience with Agile software development
Ability to work independently and across multiple teams
Proficiency in using GCP SDKs for interacting with native services
Experience in design and development of large scale data solutions using GCP services like DataProc, Dataflow, Cloud Bigtable, BigQuery,
Cloud SQL, Pub/Sub, Cloud Data Fusion, Cloud Composer, Cloud Functions, Cloud storage, Compute Engine, Cloud IAM and Cloud Logging
Experience with Git and CI/CD pipelines using jenkins, cloud Build, cloud Run
Expert level skills in writing and optimizing SQL and stored procedures
Gook understanding on SQL Queries performance techniques
Good understanding of data warehousing concepts, architectural best practices, design patterns and performance tuning
Experience in big data technologies and tools such as Teradata, SAP HANA, Snowflake, Spark/PySpark, Kafka
Experience in Data Modeling techniques and approaches like LDM & PDM, Erwin, etc.
Strong hands on experience on Enterprise Data Foundation technologies and tools such as Teradata, SAP HANA, Snowflake, GCP BigQuery
Experience building data processing pipelines to integrate large datasets from multiple sources and formats
Experience designing and developing data pipelines from ingestion to consumption within big data architecture using Python, Java, SQL etc.
Experience in designing and implementing solutions across various Cloud services such as GCE, GKE, cloud run, BigQuery, Dataproc, Dataflow, Dataplex, CloudSQL, Cloudspanner
Experience with building data pipelines in streaming and batch mode
Experience with database management, migration and transformation to cloud native DBs like Cloud SQL, Spanner,
Experience in implementing enterprise data concepts such as Master Data Management and Enterprise Data Warehouse, experience with MDM standards.
Implementing cloud data solutions in the context of business applications, cost optimization, client’s strategic needs and future growth goals as it relates to becoming a ‘data driven’ organization
Understanding of emerging technologies and latest cloud providers (GCP & AWS) services & solutions
Use an analytical and data driven approach to drive a deep understanding of fast changing business
Experience in development using message queues (cloud pub sub), stream processing, highly available and fault tolerant techniques
Good knowledge and hands on experience on Data Build Tool ( DBT) and Informatica to build ELT data pipelines.
Nice to have skills:
- Cisco Process and Data understanding like IB Data, Service contract Management, Auto Renewals, Services Domain, Booking, Quotes, Digital Case Services, Quote to Cash, Invoicing, Licensing, and Provisioning, Sales Compensation, Software and Recurring Revenue etc.
- GCP Architect and Data Engineer – Certifications
- Experience/Knowledge with reporting technologies (i.e. Tableau, PowerBI, Erwin, Informatica) is an added advantage.
- Good to have Hi-Tech Manufacturing domain experience.
Primary Location: India-Maharashtra-Pune
Job Posting: Oct 3, 2022
Experience Required (In Years): Minimum– 12 Maximum– 18
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