Senior Cloud-Native Data Architect

1 week ago

Nellore, Andhra Pradesh, India beBeeData Full time ₹ 12,24,000 - ₹ 21,42,000

Role Description

A key objective of this position is to design and implement scalable, robust, and secure data pipelines utilizing cloud-native services. As a Senior Data Engineer, you will work on designing, developing, and optimizing data ingestion, transformation, and governance frameworks, enabling real-time and batch data analytics across our data platform.

This role plays a pivotal part in the data engineering team and requires strong expertise in building scalable data architectures, implementing enterprise-grade data governance, security, and AI-powered engineering automation. Key responsibilities include:

  • 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.

In addition to technical skills, strong problem-solving, communication, and stakeholder collaboration skills are required. The ideal candidate should be proactive in learning and adopting emerging technologies in data & AI, have a consultative approach, and be socially confident. A Bachelor's degree in Computer Science or related field and 4-8 years' experience in Data Engineering are preferred.

Key Technical Skills

  • Proficiency in SQL, PySpark, Python, and data orchestration tools.
  • 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.

Personal Attributes/Traits

  • Consultative
  • Socially confident
  • Achievement oriented
  • Decisive and action-oriented
  • Creative
  • Eager to learn
  • Resilient

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