Senior Enterprise Data Architect

6 days ago

Vizag, Andhra Pradesh, India beBeeData Full time US$ 18,00,000 - US$ 20,00,000
Job Summary

We are seeking an experienced Data Architect to join our team. The successful candidate will be responsible for designing and implementing end-to-end data pipelines and data integration solutions for various structured and unstructured data sources and targets.

Main Responsibilities:
  • Design and Implement Data Solutions: The Data Architect will design and implement scalable data warehouse solutions on cloud-based platforms such as Big Query or Redshift.
  • Data Integration and Migration: The candidate will have experience in architecting, designing, and implementing data integration, storage, and data pipeline toolsets like S3, Cloud Storage, Athena, Glue, Sqoop, Flume, Hive, Kafka, Pub-Sub, Kinesis, Dataflow, DataProc, Airflow, Composer, Spark SQL, Presto, EMRFS, etc.
  • Business Intelligence and Analytics: The successful candidate will have a 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.
  • Cloud Security: The candidate will understand security features and policies in one or more cloud environments like GCP/AWS/Azure.
  • Project Management: The Data Architect will lead multiple data engagements on GCP Cloud for data lakes, data engineering, data migration, data warehouse, and business intelligence.

Requirements:
  • Strong Communication Skills. Strong communication and articulation skills.
  • Leadership Skills. Good leadership skills.
  • Team Player. Should be a good team player.
  • Analytical Skills. Good analytical and problem-solving skills.

Preferred Qualifications:
  • 5+ Years of Experience. 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).
  • Cloud Technologies. Well-versed with various data integration and ETL technologies on cloud like Spark, PySpark/Scala, Dataflow, DataProc, EMR, etc. on various clouds.
  • Traditional ETL Tools. Experience of having worked with traditional ETL tools like Informatica/DataStage/OWB/Talend, etc.
  • Cloud Databases. 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.
  • No-SQL Databases. Exposure to any of the No-SQL databases like Mongo dB, CouchDB, Cassandra, Graph dB, etc.
  • Machine Learning Frameworks. Preferred experience of having worked on machine learning frameworks like TensorFlow, PyTorch, etc.

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