Data platform architect
About the role
Job Description
Key Responsibilities
- Design and implement scalable data platform architectures on
Microsoft Azure
.
- Lead the design, setup, and implementation of
Databricks-based data platforms
.
- Develop and optimize data processing frameworks using
Databricks, Spark SQL, PySpark, and Python
.
- Design, build, and maintain robust
ETL/ELT pipelines
Azure Data Factory
and related Azure data services.
- Define data lake, lakehouse, and data warehouse architecture patterns to support enterprise data needs.
- Implement data ingestion, transformation, orchestration, and publishing processes across structured and semi-structured data sources.
- Establish best practices for data platform development, deployment, monitoring, security, and performance optimization.
- Partner with business and technical teams to translate data requirements into scalable technical solutions.
- Optimize data pipelines and Spark workloads for performance, reliability, and cost efficiency.
- Support data governance, access control, data quality, metadata management, and platform security requirements.
- Create architecture documentation, technical design documents, standards, and operational guidelines.
- Provide technical guidance to data engineers and project teams on modern data platform practices.
Required Qualifications
5+ years of experience
in data platform architecture, data engineering, cloud data solutions, or related roles.
- Strong experience with
Microsoft Azure data services
.
- Hands-on experience with
Azure Data Factory
for data integration, orchestration, and pipeline development.
- Proven experience in
Databricks platform design, implementation, administration, and optimization
.
- Strong programming skills in
Python
.
- Solid experience with
Spark SQL, PySpark, and distributed data processing
.
- Experience designing and implementing
ETL/ELT pipelines
for enterprise-scale data environments.
- Good understanding of data lake, lakehouse, and data warehouse architecture.
- Experience working with large-scale data processing, data modeling, and data integration patterns.
- Strong knowledge of data platform performance tuning, monitoring, and troubleshooting.
- Ability to communicate effectively with both technical and non-technical stakeholders.
- Strong analytical, problem-solving, and solution design skills.
Preferred Qualifications
- Experience with
Delta Lake, Unity Catalog, Databricks Workflows, Auto Loader, and Lakehouse architecture
.
- Experience with
Azure Data Lake Storage, Azure Synapse Analytics, Azure Key Vault, Event Hub, or related Azure services
.
- Familiarity with CI/CD, Git, DevOps practices, Terraform, or infrastructure-as-code.
- Experience with data governance, data quality frameworks, metadata management, and access control.
- Experience building enterprise data platforms from the ground up.
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