Chief Data Architect

6 days ago

Delhi, Delhi, India beBeeDataEngineer Full time ₹ 1,50,00,000 - ₹ 2,50,00,000
Job Overview

We're seeking a skilled Data Engineer to build and maintain data pipelines, design data models, and ensure the performance, reliability, and scalability of our analytics infrastructure.

The ideal candidate will have strong experience with AWS services, a solid understanding of SQL and data modeling, and familiarity with BI tools like QuickSight.

They will collaborate with engineers, product, and design to deliver insights quickly and automate scheduled reporting workflows and exports for clients and admins.

Key Responsibilities
  • Data Pipelines: Design and implement data pipelines connecting Aurora MySQL to Redshift Serverless, S3, and QuickSight.
  • Data Modeling: Develop data models, materialized views, and APIs to enable fast reporting and analytics.
  • Scheduled Reporting: Automate scheduled reporting workflows and exports for clients and admins.
  • Collaboration: Collaborate with cross-functional teams to deliver insights quickly.
  • Infrastructure Performance: Ensure the performance, reliability, and scalability of our analytics infrastructure.
Requirements
  • AWS Experience: Strong experience with AWS services, including Aurora, Redshift, S3, Lambda, and EventBridge.
  • SQL and Data Modeling: Solid understanding of SQL and data modeling, including fact/dimension schemas and materialized views.
  • BI Tools: Familiarity with BI tools like QuickSight, Metabase, or Superset.
  • IAM and Security: Good understanding of IAM, security, and data governance principles.
Nice to Have
  • Python Experience: Experience with Python and libraries like awswrangler for data automation.
  • ETL/ELT Frameworks: Exposure to ETL/ELT frameworks like Glue, Airflow, or dbt.
  • Data Lake Best Practices: Knowledge of data lake best practices, including Parquet and partitioning.
  • Infrastructure-as-Code: Comfort with infrastructure-as-code using Terraform or CDK.
  • SaaS Reporting Architectures: Understanding of multi-tenant SaaS reporting architectures.

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