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 Data Ops/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 Dev Ops.
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 Data Ops 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, Py Spark , 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 Data Ops/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 Dev Ops.
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 Data Ops 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, Py Spark , 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 Linked In 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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