Highly Skilled Data Architect

4 days ago

Malappuram, Kerala, India beBeeDataEngineering Full time ₹ 1,00,00,000 - ₹ 2,00,00,000
Senior Data Engineer Role

We are seeking a Senior Data Engineer to 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.

  • Design and implement scalable, robust, and secure data pipelines using Azure Data Factory, Databricks, Synapse Analytics, Azure Data Lake Gen2, Event Hub, and Azure Functions.
  • 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.

The ideal candidate will have deep expertise in building scalable data pipelines, implementing enterprise-grade data governance, security, and AI-powered engineering automation. Proficiency in SQL, PySpark, Python, and data orchestration tools is required. Strong understanding of data architecture patterns – Lakehouse, medallion, delta architecture – is also necessary.

Key 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.

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