Chief Data Innovation Officer

5 days ago

Vellore, Tamil Nadu, India beBeeData Full time ₹ 20,00,000 - ₹ 25,00,000
Senior Data Engineer Job Description

We are seeking a Senior Data Engineer to design, develop, and optimize data ingestion, transformation, and governance frameworks using cloud-native technologies.

This role will play a pivotal part in building scalable data pipelines, implementing enterprise-grade data governance, security, and AI-powered engineering automation on Microsoft Azure, AWS, and GCP.

Key Responsibilities:

  • Designing and implementing robust and secure data pipelines using Azure Data Factory, Databricks, Synapse Analytics, and Azure Data Lake Gen2.
  • Developing and maintaining ETL/ELT processes for structured and unstructured data, as well as implementing Change Data Capture (CDC), streaming pipelines, and batch ingestion.
  • Working with AWS Glue, S3, Redshift or GCP BigQuery, Dataflow as needed, and optimizing performance and cost across data workloads and cloud environments.
  • Establishing and maintaining data quality frameworks, observability tools, and monitoring dashboards, and defining and enforcing data rules, validations, anomaly detection, and reconciliation.
  • Implementing data lineage and metadata tracking using Azure Purview, driving adoption of data cataloguing, profiling, and classification tools, and collaborating with data stewards and compliance teams to ensure governance alignment.

Qualifications:

  • 4+ years in data engineering with at least 2+ years on Azure cloud platform, hands-on experience with Azure Data Factory, Azure Data Lake Gen2, Databricks, Synapse, Purview, and proficiency in SQL, PySpark, Python, and data orchestration tools.
  • A 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, and exposure to GenAI or agentic AI to Automate data cataloguing and metadata enrichment etc.

Soft Skills:

  • Strong problem-solving, communication, and stakeholder collaboration skills.
  • Ability to lead data initiatives and mentor team members.
  • Proactive in learning and adopting emerging technologies in data & AI.

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