Azure Data architect

Cognizant; Chicago (IL); Hybrid; USD 120,000 - 160,000; Full time

Job summary

Cognizant is seeking a seasoned Data Architect to design scalable enterprise data platforms on Azure, using Databricks, Delta Lake and modern lakehouse patterns.

The role requires leading data modernization initiatives, defining architecture standards, governance, and mentoring engineers. This position is onsite in Chicago with hybrid collaboration 3 days per week.

Qualifications

• 8+ years in data engineering/architecture.
• Hands-on Spark/PySpark and SQL expertise.
• Experience designing Delta Lake and lakehouse architectures.
• Experience implementing Medallion Architecture.
• Strong data governance, metadata management & data quality.
• Experience with distributed data processing at scale.
• CI/CD, Git, DevOps and deployment automation.
• Excellent communication and stakeholder management.

Responsibilities

• Design and implement enterprise-scale Data Lakehouse solutions on Azure.
• Define Bronze/Silver/Gold layers per Medallion Architecture.
• Lead ETL/ELT pipelines with Spark/PySpark.
• Establish data ingestion for batch and near real-time.
• Define governance, security, lineage, metadata standards.
• Collaborate with stakeholders to translate requirements.
• Perform performance tuning and workload management.
• Mentor teams on Databricks and cloud data engineering.

Skills

Spark / PySpark

SQL

Delta Lake

Medallion Architecture

Data governance

Metadata management

CI/CD

DevOps

Stakeholder management

Tools

Git

Terraform

CI/CD tooling

Job description

Location : Chicago, IL (Work from Office)

• Candidates must work from the Chicago office.
• Hybrid candidates must be available for regular onsite collaboration at least 3 days per week.
• Preference will be given to candidates located in or near Chicago.

Job Summary

We are seeking a highly skilled Data Architect with strong expertise in Azure Databricks, Delta Lake, Spark/PySpark, and Modern Data Lakehouse Architectures. The ideal candidate will be responsible for designing scalable enterprise data platforms, defining data architecture standards, implementing Medallion Architecture, and leading large-scale data modernization initiatives on Azure.

Key Responsibilities

• Design and implement enterprise-scale Data Lakehouse solutions using Azure Databricks and Delta Lake.
• Define and manage Bronze, Silver, and Gold layers following Medallion Architecture best practices.
• Design Delta Lake tables, partitioning strategies, data models, and storage optimization techniques.
• Architect scalable ETL/ELT pipelines using Spark and PySpark.
• Establish data ingestion frameworks for batch and near real-time data processing.
• Implement schema evolution, schema enforcement, and data quality validation mechanisms.
• Define data governance, security, lineage, metadata, and access control standards.
• Collaborate with business stakeholders, data engineers, analysts, and product teams to translate requirements into scalable solutions.
• Perform performance tuning using partitioning, caching, optimization, and workload management techniques.
• Lead architecture reviews, design discussions, and technical governance processes.
• Mentor engineering teams on Databricks and cloud data engineering best practices.

Required Skills

• 8+ years of experience in Data Engineering/Data Architecture.
• Strong hands-on experience with:
• Spark / PySpark
• SQL
• Expertise in designing Delta Tables and Lakehouse architecture.
• Experience implementing Medallion Architecture.
• Strong understanding of schema evolution, data quality frameworks, and metadata management.
• Experience with distributed data processing and large-scale datasets.
• Strong knowledge of CI/CD, Git, DevOps, and deployment automation.
• Excellent communication and stakeholder management skills.

Preferred Skills

• Unity Catalog
• Structured Streaming
• Kafka/Event Hub
• MLflow
• Terraform or Infrastructure as Code

Additional Hiring Criteria

• Strong communication and client-facing skills.
• Ability to work independently in a fast-paced environment.
• Willingness to work onsite in Chicago at least 3 days per week.
• Candidates seeking fully remote opportunities will not be considered.
• Local Chicago candidates are highly preferred. Non-local candidates must demonstrate commitment to the onsite work requirement.