Job Description
Job Title
Senior Data Architect / Lead Data Engineer – Azure & Databricks
Job Summary
We are seeking an experienced Senior Data Architect / Lead Data Engineer to design, build, and lead cloud-native data platforms on Azure , with a strong focus on Databricks . The role involves architecting end-to-end modern data solutions, leading data strategy initiatives, enabling DataOps/MLOps practices, and collaborating closely with customers and internal teams to drive data modernization at scale.
Key Responsibilities
Design and develop modern, cloud-native data architectures to support analytics, BI, and advanced insights.
Build and optimize cost-effective data infrastructure using Azure Databricks .
Orchestrate data workflows using Databricks Workflows and Azure Data Factory (ADF) .
Lead data strategy and architecture discussions focused on scalability, performance, and flexibility.
Design and implement CI/CD pipelines for Databricks using Azure DevOps .
Partner with customers to deliver data modernization and migration solutions .
Develop training plans and learning materials to upskill internal associates.
Build industry-specific and domain-driven data solutions tailored to customer needs.
Design and implement a Smart Operations framework covering DataOps and MLOps best practices.
Collaborate with Data Engineering, Data Management, BI, and Analytics teams in complex enterprise environments.
Required Skills & Experience
10+ years of overall experience in data engineering and analytics, with at least 4+ years delivering cloud-native, end-to-end data solutions (ingestion to consumption).
Strong hands-on experience architecting and implementing Modern Data Platforms on Azure .
Advanced experience with Databricks, PySpark , and distributed data processing frameworks.
Proven expertise in cloud-native architecture , data governance, and security.
Extensive experience migrating on-premises data platforms (Hadoop, Spark) to Azure Databricks .
Strong understanding of data warehouse concepts , including columnar database architectures .
Hands-on experience with ETL/ELT tools , Kafka or streaming platforms , and modern data integration patterns.
Solid understanding of Agile/Scrum methodologies and working in iterative delivery models.
Ability to collaborate across cross-functional teams in a large-scale IT ecosystem.
Preferred / Added Advantage
Experience designing and implementing Data Mesh architectures and Data Products .
Exposure to industry-specific data solutions .
Knowledge of advanced analytics and ML enablement on cloud data platforms.
If you want, I can also:
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Senior Data Architect / Lead Data Engineer – Azure & Databricks
Job Summary
We are seeking an experienced Senior Data Architect / Lead Data Engineer to design, build, and lead cloud-native data platforms on Azure , with a strong focus on Databricks . The role involves architecting end-to-end modern data solutions, leading data strategy initiatives, enabling DataOps/MLOps practices, and collaborating closely with customers and internal teams to drive data modernization at scale.
Key Responsibilities
Design and develop modern, cloud-native data architectures to support analytics, BI, and advanced insights.
Build and optimize cost-effective data infrastructure using Azure Databricks .
Orchestrate data workflows using Databricks Workflows and Azure Data Factory (ADF) .
Lead data strategy and architecture discussions focused on scalability, performance, and flexibility.
Design and implement CI/CD pipelines for Databricks using Azure DevOps .
Partner with customers to deliver data modernization and migration solutions .
Develop training plans and learning materials to upskill internal associates.
Build industry-specific and domain-driven data solutions tailored to customer needs.
Design and implement a Smart Operations framework covering DataOps and MLOps best practices.
Collaborate with Data Engineering, Data Management, BI, and Analytics teams in complex enterprise environments.
Required Skills & Experience
10+ years of overall experience in data engineering and analytics, with at least 4+ years delivering cloud-native, end-to-end data solutions (ingestion to consumption).
Strong hands-on experience architecting and implementing Modern Data Platforms on Azure .
Advanced experience with Databricks, PySpark , and distributed data processing frameworks.
Proven expertise in cloud-native architecture , data governance, and security.
Extensive experience migrating on-premises data platforms (Hadoop, Spark) to Azure Databricks .
Strong understanding of data warehouse concepts , including columnar database architectures .
Hands-on experience with ETL/ELT tools , Kafka or streaming platforms , and modern data integration patterns.
Solid understanding of Agile/Scrum methodologies and working in iterative delivery models.
Ability to collaborate across cross-functional teams in a large-scale IT ecosystem.
Preferred / Added Advantage
Experience designing and implementing Data Mesh architectures and Data Products .
Exposure to industry-specific data solutions .
Knowledge of advanced analytics and ML enablement on cloud data platforms.
If you want, I can also:
Tighten this for ATS optimization
Convert it into a short LinkedIn job post
Tailor it for consulting / client-facing roles
Align it to a specific company or industry
Just say the word.
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