Cloud Engineering Lead

5 days ago

Hubli, Karnataka, India beBeeEngineering Full time ₹ 1,50,00,000 - ₹ 2,00,00,000
Job Summary

We are seeking a highly skilled Cloud Engineering Lead to drive the design and implementation of scalable, robust, and secure cloud-native data engineering solutions.

The ideal candidate will have deep expertise in building cloud-based data pipelines, implementing enterprise-grade data governance, security, and AI-powered engineering automation.

This role will play a pivotal part in designing, developing, and optimizing data ingestion, transformation, and governance frameworks, enabling real-time and batch data analytics across our data platform.

Key Responsibilities:
  • Design and implement scalable, robust, and secure cloud-native data pipelines using cloud services such as Azure Data Factory, Databricks, and Synapse Analytics.
  • Develop and maintain ETL/ELT processes for structured and unstructured data.
  • Implement Change Data Capture (CDC), streaming pipelines, and batch ingestion.
  • Work with AWS Glue, S3, Redshift or GCP BigQuery, Dataflow as needed.
  • Optimize performance and cost across data workloads and cloud environments.
  • Establish and maintain data quality frameworks, observability tools, and monitoring dashboards.
  • Define and enforce data rules, validations, anomaly detection, and reconciliation.
  • Implement data lineage and metadata tracking using Azure Purview.
  • Drive adoption of data cataloguing, profiling, and classification tools.
  • Collaborate with data stewards and compliance teams to ensure governance alignment.
  • Implement role-based access control (RBAC), data masking, encryption, and tokenization.

Key Skills include technical design, coding, unit testing, test case documentation, and walkthroughs for all assigned cloud-related projects. Additionally, the role requires critical evaluation of information gathered from multiple sources, reconciling conflicts, decomposing high-level information into details, abstracting up from low-level information to a general understanding, and distinguishing user requests from underlying true needs.

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