Chief Cloud Data Architect

We are seeking a seasoned senior data engineer to join our team. The ideal candidate will have a strong background in cloud-native data engineering, with a focus on Microsoft Azure and familiarity with AWS and GCP.

This role will 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.

The selected candidate will be responsible for technical design, coding, unit testing, test case documentation, and walkthroughs for all assigned Azure-related projects to support business and operational needs.

They will also collaborate with developers and subject matter experts to establish the technical vision and analyze trade-offs between usability and performance needs.

Additionally, they will mentor junior data engineers and contribute to technical best practices.

Key Responsibilities:

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

Qualifications & Experience:

• 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.

Requirements:

• BE/BTech/MCA degree with 4 to 8 years' experience in Data Engineering
• 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

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

Skills:

• Microsoft Azure
• Cloud-Native Data Engineering
• Data Governance
• Security
• AI-Powered Engineering Automation
• Machine Learning
• NLP or LLMs

What We Offer:
Competitive compensation and benefits package.
Opportunities for professional growth and development.
Collaborative and dynamic work environment.