Cloud Data Engineering Expert

1 day ago

Ajmer, Rajasthan, India beBeeCloudDataEngineering Full time ₹ 15,50,000 - ₹ 26,10,000

Job Title: Cloud Data Engineering Expert

Description:

We are seeking a highly skilled cloud data engineer to join our team and drive the design, development, and optimization of scalable data ingestion, transformation, and governance frameworks.

This role will play a pivotal part in enabling real-time and batch data analytics across our data platform. The ideal candidate will have deep expertise in building robust and secure data pipelines, implementing enterprise-grade data governance, security, and AI-powered engineering automation.

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.

Required Skills and Qualifications:

  • 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.
Benefits:

The successful candidate will have the opportunity to work on cutting-edge technologies and contribute to the development of innovative solutions. They will also have access to ongoing training and professional development opportunities.

We offer a dynamic and collaborative work environment, with a strong focus on teamwork and open communication.

The role is located in [location], with regular travel to other sites as required.

Please note that this job description may be subject to change based on business needs and requirements.

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