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Senior Cloud Native Data Engineer

3 weeks ago

Davangere, Karnataka, India beBeeData Full time US$ 80,000 - US$ 1,50,000

Job Overview:

We are seeking a highly skilled Senior Data Engineer to fill a pivotal role in our organization.

The ideal candidate will have a strong background in cloud-native data engineering, primarily on Microsoft Azure, and familiarity with AWS and GCP.

The successful candidate will design, develop, and optimize data ingestion, transformation, and governance frameworks, enabling real-time and batch data analytics across our data platform.

The role will play a crucial part in building scalable data pipelines, implementing enterprise-grade data governance, security, and AI-powered engineering automation.

The Senior Data Engineer will work closely with developers and subject matter experts to establish the technical vision and analyze trade-offs between usability and performance needs.

The ideal candidate will have hands-on experience with Azure Data Factory, Azure Data Lake Gen2, Databricks, Synapse, Purview, and proficiency in SQL, PySpark, Python, and data orchestration tools.

Strong understanding of data architecture patterns – Lakehouse, medallion, delta architecture is also required.

The successful candidate will be responsible for technical design, coding, unit testing, test case documentation, and walkthroughs for all assigned Azure related projects.

The ideal candidate will also be able to critically evaluate information gathered from multiple sources, reconcile conflicts, decompose high-level information into details, abstract up from low-level information to a general understanding, and distinguish user requests from the underlying true needs.

The Senior Data Engineer will mentor junior data engineers and contribute to technical best practices.

  • 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
  • Responsible for technical design, coding, unit testing, test case documentation, and walkthroughs for all assigned Azure related projects

Requirements:

  • 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.
  • Experience with NLP or LLMs in metadata extraction or data classification is a plus

Personal Attributes/Traits:

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

Competencies:

  • Business Foresight
  • Influencing Others
  • Fostering Partnerships With Customers
  • Managing Transformation
  • Driving Excellence
  • Leading Teams
  • Working Across Boundaries