Data Engineer

2 days ago

Ahmedabad, Gujarat, India beBeeData Full time ₹ 30,00,000 - ₹ 40,00,000
Technical Data Lead

As a Technical Data Lead, you will play a crucial role in leading multiple data engagements on Google Cloud Platform (GCP) for data lakes, data engineering, data migration, data warehouse, and business intelligence. The successful candidate will have more than 8 years of experience in technical, solutioning, and analytical roles with a strong background in data integration and architecture.

Key Responsibilities:

  1. Lead multiple data projects on GCP Cloud for data lakes, data engineering, data migration, data warehouse, and business intelligence.
  2. Interface with various stakeholders to understand the data requirements.
  3. Oversee the successful delivery of all allocated projects based on Schedule, Quality, and Customer Satisfaction.
  4. Be responsible for the design and development of distributed, high volume multi-thread batch, real-time, and event processing systems.
  5. Implement processes and systems to validate data, monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it.
  6. Collaborate with the Pre-Sales team on RFPs and RFIs, helping them by creating solutions for data.
  7. Mentor junior talent within the team, define and track their growth parameters.
  8. Contribute to building assets and accelerators.

Requirements:

  1. More than 8 years of experience in technical, solutioning, and analytical roles.
  2. 5+ years of experience in building and managing Data Lakes, Data Warehouse, Data Integration, Data Migration and Business Intelligence/Artificial Intelligence solutions on Cloud (GCP/AWS/Azure).
  3. Experience in architecting, designing, and implementing end-to-end data pipelines and data integration solutions for varied structured and unstructured data sources and targets.
  4. Proficiency in various Data Integration, and ETL technologies on Cloud like Spark, Pyspark/Scala, Dataflow, DataProc, EMR, etc. on various Cloud.
  5. Deep knowledge of one or more Cloud and On-Premise Databases like Cloud SQL, Cloud Spanner, Big Table, RDS, Aurora, DynamoDB, Oracle, Teradata, MySQL, DB2, SQL Server, etc.
  6. Exposure to any of the No-SQL databases like MongoDB, CouchDB, Cassandra, Graph dB, etc.
  7. Experience in architecting and designing scalable data warehouse solutions on cloud on Big Query or Redshift.
  8. Good understanding of Cloud solutions for Iaas, PaaS, SaaS, Containers and Microservices Architecture and Design.
  9. Ability to compare products and tools across technology stacks on Google, AWS, and Azure Cloud.
  10. Good understanding of BI Reporting and Dashboarding and one or more toolsets associated with it like Looker, Tableau, Power BI, SAP BO, Cognos, Superset, etc.
  11. Understanding of Security features and Policies in one or more Cloud environments like GCP/AWS/Azure.

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