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Cloud Data Engineer

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Senior Data Architect Position

A forward-thinking Senior Data Architect is sought after to design and implement scalable, secure, and robust data architectures that enable real-time and batch analytics across our data platform. The ideal candidate will have deep expertise in building cloud-native 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, leveraging Azure Data Factory, Databricks, Synapse Analytics, and other cutting-edge technologies. A strong understanding of data architecture patterns such as Lakehouse, medallion, delta architecture is also essential.

Key Responsibilities:
  • Design and implement scalable, robust, and secure data pipelines using Azure Data Factory, Databricks, Synapse Analytics, and other tools.
  • Develop and maintain ETL/ELT processes for structured and unstructured data, ensuring high-quality data pipelines.
  • Implement Change Data Capture (CDC), streaming pipelines, and batch ingestion, utilizing Azure Event Hub and Azure Functions.
  • Work with AWS Glue, S3, Redshift or GCP BigQuery, Dataflow as needed, and optimize performance and cost across data workloads and cloud environments.
  • Establish and maintain data quality frameworks, observability tools, and monitoring dashboards, driving adoption of data cataloguing, profiling, and classification tools.
  • Define and enforce data rules, validations, anomaly detection, and reconciliation, implementing role-based access control (RBAC), data masking, encryption, and tokenization.
  • Collaborate with data stewards and compliance teams to ensure governance alignment, responsible for technical design, coding, unit testing, test case documentation, and walkthroughs for all assigned Azure-related projects.
Qualifications & Experience:
  • 4+ years in data engineering with at least 2+ years on Azure cloud platform experience.
  • Hands-on experience with Azure Data Factory, Azure Data Lake Gen2, Databricks, Synapse, Purview, 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.