Cognizant (NASDAQ: CTSH) is a leading provider of information technology, consulting, and business process outsourcing services, dedicated to helping the world's leading companies build stronger businesses. Headquartered in Teaneck, New Jersey (U.S.). Cognizant is a member of the NASDAQ-100, the S&P 500, the Forbes Global 1000, and the Fortune 500 and we are among the top performing and fastest growing companies in the world.
This role does not support visa-dependent candidates, either now or in the foreseeable future.
Full time
Hybrid
Washington, DC
Azure Data Engineer / Azure Data Architect
Job Description
Location: Hybrid / Remote
Experience: 8+ Years
Employment Type: Full-Time
Position Overview
We are seeking an experienced Azure Data Engineer / Data Architect with strong expertise in designing, building, and optimizing enterprise-scale data platforms within the Microsoft Azure ecosystem. The ideal candidate will have extensive hands-on experience with Azure Databricks, Azure Data Factory, Azure Data Lake, SQL, Data Warehousing, and Modern Data Architecture patterns.
This role requires a combination of deep technical expertise, architectural leadership, and hands-on development capabilities to design scalable, governed, and high-performing data solutions supporting analytics, reporting, AI/ML, and business operations.
Key Responsibilities
Data Architecture & Platform Design
- Design and develop scalable, secure, and reusable enterprise data architectures using Azure cloud technologies.
- Define technical architecture standards, design patterns, and best practices for enterprise data platforms.
- Build scalable Lakehouse architectures utilizing Azure Data Lake Storage and Azure Databricks.
- Design and implement Medallion Architecture (Bronze, Silver, Gold Layers) for modern analytics platforms.
- Create high-level solution designs, data models, architecture diagrams, and technical documentation.
- Lead architecture reviews and provide technical governance across multiple projects.
Azure Databricks Development (Must Have)
Architecture & Administration
- Design and manage Azure Databricks environments, clusters, compute resources, and workspaces.
- Develop and maintain enterprise-scale Lakehouse solutions.
- Implement Delta Lake architecture and optimize Delta Table performance.
- Utilize Databricks Unity Catalog for enterprise-wide data governance and metadata management.
- Configure and manage security, access controls, and data lineage capabilities.
Data Engineering
- Develop PySpark-based ETL/ELT pipelines for large-scale structured and semi-structured datasets.
- Read, transform, validate, and write data using Spark DataFrames and Delta Tables.
- Implement data quality, audit, and reconciliation frameworks using SQL and PySpark.
- Apply Databricks performance tuning and optimization techniques including:
- Partitioning
- Z-Ordering
- Data Skipping
- Caching
- Auto Optimize
- VACUUM & OPTIMIZE commands
Emerging Technologies
- Stay current with Databricks innovations including:
- Lakehouse Architecture
- Lakeflow
- Delta Live Tables
- Unity Catalog
- Databricks Genie
- Exposure to AI/ML workloads and LLM-based implementations within Databricks environments is highly desirable.
Azure Data Factory (ADF)
- Design and implement enterprise-grade ADF pipelines and orchestration frameworks.
- Develop dynamic and metadata-driven data ingestion pipelines.
- Build solutions to migrate data from on-premise applications and databases to Azure platforms.
- Implement failure handling, monitoring, alerting, and notification frameworks.
- Create parameterized reusable pipeline templates.
- Develop scheduling, dependency management, and workflow orchestration mechanisms.
- Implement Slowly Changing Dimension (SCD) Type 2 solutions using ADF, SQL, and Azure Databricks.
SQL & Data Processing
- Design and optimize complex SQL solutions supporting enterprise reporting and analytics.
- Utilize advanced SQL analytical functions and windowing functions.
- Implement and optimize joins, aggregations, subqueries, Common Table Expressions (CTEs), and Self Joins.
- Perform SQL performance tuning, indexing, query optimization, and execution plan analysis.
- Develop reusable stored procedures, views, and database objects supporting enterprise applications.
Data Warehousing & Modeling
- Design enterprise data warehouse solutions using industry-standard modeling techniques.
- Develop:
- Fact Tables
- Dimension Tables
- Slowly Changing Dimensions (Type 1, 2, and 3)
- Aggregate Structures
- Implement and maintain:
- Star Schema
- Snowflake Schema
- Data Vault Models
- Dimensional Models
- Understand and apply normalization and denormalization strategies for OLTP and OLAP environments.
Governance & Best Practices
- Establish and enforce enterprise data engineering standards and best practices.
- Define governance models for data quality, metadata, lineage, and security.
- Implement monitoring, auditing, and operational controls across the data platform.
- Collaborate with security and governance teams to ensure compliance with enterprise standards.
- Drive adoption of automated testing, CI/CD pipelines, and release automation for data platforms.
Stakeholder Engagement
- Collaborate with business stakeholders, enterprise architects, project managers, and development teams.
- Provide architecture guidance, technical leadership, and solution recommendations.
- Evaluate emerging technologies and provide strategic recommendations for platform modernization.
- Lead technical workshops, architecture reviews, and design discussions.
Required Qualifications
Education
- Bachelor's or Master's Degree in:
- Computer Science
- Information Systems
- Engineering
- Related Technical Discipline
Experience
- 8+ years of experience in Data Engineering, Data Architecture, or Enterprise Data Warehousing.
- Proven experience designing and implementing Azure-based enterprise data platforms.
- Strong understanding of large-scale data processing and cloud-native architectures.
Required Technical Skills
Azure Technologies
- Azure Databricks
- Azure Data Factory (ADF)
- Azure Data Lake Storage Gen2 (ADLS)
- Azure Synapse Analytics
- Azure SQL Database
- Azure Functions
- Azure Logic Apps
Data Engineering
- PySpark
- Spark SQL
- Delta Lake
- Unity Catalog
- Delta Live Tables
- ETL/ELT Design Patterns
- Data Quality Frameworks
Database Technologies
- SQL Server
- Oracle
- PostgreSQL
Programming
- Python
- SQL
- PySpark
Data Warehousing
- Dimensional Modeling
- Star Schema
- Snowflake Schema
- Data Vault
- Medallion Architecture
- SCD Type 1/2/3
DevOps & Automation
- Azure DevOps
- CI/CD Pipelines
- ARM Templates
- PowerShell
- Azure Automation
- AZ Copy
Application Accepted: 8/20/2026
This position is also eligible for Cognizant’s discretionary annual incentive program, based on performance and subject to the terms of Cognizant’s applicable plans.
Benefits: Cognizant offers the following benefits for this position, subject to applicable eligibility requirements:
· Medical/Dental/Vision/Life Insurance
· Paid holidays plus Paid Time Off
· 401(k) plan and contributions
· Long-term/Short-term Disability
· Paid Parental Leave
· Employee Stock Purchase Plan
Disclaimer: The salary, other compensation, and benefits information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable la
Our strength is built on our ability to work together. Our diverse backgrounds offer different perspectives and new ways of thinking. It encourages lively discussions, creativity, productivity, and helps us build better solutions for our clients. We want someone who thrives in this setting and is inspired to craft meaningful solutions through true collaboration.
If you are content with ambiguity, excited by change, and excel through autonomy, we’d love to hear from you!
关于高知特 (Cognizant)
高知特(Cognizant)（纳斯达克代码：CTSH）作为一家AI Builder和相关技术服务提供商，致力于通过打造全栈AI解决方案，帮助企业将人工智能投资转化为实际价值。公司凭借深厚的行业经验、流程优化和工程技术专长，将企业独特的业务场景融入科技系统，赋能组织释放人才潜能，推动切实成果，并帮助全球企业在瞬息万变的环境中保持领先。如需了解更多详情，敬请访问 cognizant.ai 或关注@cognizant。
补充雇佣信息
薪酬信息截至本职位发布之日为准。Cognizant 保留在适用法律允许的范围内随时修改该信息的权利。
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