Senior Cloud-Native Data Architect

1 week ago

Aligarh, Uttar Pradesh, India beBeeDataEngineer Full time ₹ 1,00,00,000 - ₹ 2,50,00,000

Job Opportunity:

We are seeking a skilled Data Engineer with expertise in cloud-native data engineering, primarily on Microsoft Azure. The ideal candidate will have deep knowledge of building scalable 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.

The selected candidate will be responsible for technical design, coding, unit testing, test case documentation, and walkthroughs for all assigned Azure related projects to support business and operational needs.

Key Responsibilities:

  • Design and implement scalable, robust, and secure data pipelines using Azure Data Factory, Databricks, 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

Requirements:

  • 4+ years in data engineering with at least 2+ years on Azure cloud platform
  • Hands-on with Azure Data Factory, Azure Data Lake Gen2, Databricks, Synapse, Purview
  • Proficiency in SQL, PySpark, Python, and data orchestration tools
  • Strong understanding of data architecture patterns – Lakehouse, medallion, delta architecture
  • Familiarity with Snowflake, BigQuery, Redshift, or AWS Glue
  • Experience with data versioning and GitOps for data
  • Working knowledge of data observability, lineage, cataloguing, data quality
  • Exposure to privacy-enhancing techniques, access control, security auditing
  • Exposure to machine learning use cases in data engineering pipelines, data quality, anomaly detection, and schema change detection
  • Exposure to GenAI or agentic AI to Automate data cataloguing and metadata enrichment etc.

What We Offer:

A competitive compensation package and opportunities for professional growth and development.

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