Azure Technical Lead

Cognizant; Seattle (WA); Hybrid; USD 120,000 - 135,000; Full time

Benefits offered by this job

Medical/Dental/Vision/Life Insurance

Paid holidays + PTO

401(k) plan and contributions

Disability (Long-term/Short-term)

Paid Parental Leave

Employee Stock Purchase Plan

Job summary

Cognizant in Seattle offers a hybrid Technical Lead role focusing on PySpark, Python, and Azure Databricks to design scalable data solutions and guide implementation with a focus on high-quality delivery. You will collaborate with cross-functional teams to support airline and enterprise analytics use cases with measurable business impact.

The position requires leading data engineering efforts, overseeing code quality, and mentoring engineers while ensuring alignment with enterprise data

Qualifications

• Extensive practical experience in PySpark development including transformations and large-scale processing.
• Strong proficiency in Python with modular design, error handling, logging, and cloud integration.
• Hands-on expertise with Azure Databricks including workspace configuration, job orchestration, secret management, and integration with Azure data platforms.

Responsibilities

• Design robust data engineering solutions using PySpark and Python for large-scale analytics.
• Develop reusable data pipelines on Azure Databricks supporting batch and near real-time processing.
• Translate analytical needs into technical designs aligned with enterprise data architecture.
• Oversee code reviews and enforce engineering best practices for readability and maintainability.
• Guide Azure Databricks configurations to balance cost, performance, and resilience.
• Implement testing strategies including unit and integration tests to ensure data accuracy.
• Monitor production pipelines via dashboards and alerts to minimize downtime.
• Collaborate with data scientists and analysts to deliver curated data products for analytics.
• Improve development workflows with better version control and deployment automation.
• Document designs, data models and procedures for onboarding and governance.
• Coordinate with security/compliance to adhere to governance requirements.
• Optimize Spark jobs by tuning partitions and resources for performance and cost.
• Mentor junior engineers with feedback and exposure to modern data practices.

Skills

PySpark

Python

Azure Databricks

Data engineering

Data warehousing

Mentoring

Tools

Azure Databricks

Synapse

Data Lake

Job description

Job Summary

This hybrid role is for a seasoned Technical Lead with strong hands on expertise in PySpark Python and Azure Databricks responsible for designing scalable data solutions guiding technical implementation and ensuring high quality delivery in a day shift environment while collaborating with cross functional teams to support critical airline and enterprise analytics use cases with measurable business impact.

Responsibilities

• Design robust data engineering solutions using PySpark and Python that efficiently process large scale datasets and meet strict performance expectations for business critical analytics
• Develop reusable and optimized data pipelines on Azure Databricks that support batch and near real time processing while maintaining high standards of reliability and observability
• Coordinate with product owners and business partners to translate complex analytical needs into clear technical designs that align with enterprise data architecture strategies
• Oversee code reviews and enforce engineering best practices that improve code readability maintainability and long term sustainability across multiple project teams
• Guide the selection and configuration of Azure Databricks clusters and related Azure services to balance cost performance scalability and operational resilience
• Implement rigorous testing strategies including unit integration and regression tests that ensure data accuracy and stability across evolving data sources and transformations
• Monitor production data pipelines proactively using dashboards and alerts to quickly identify issues reduce downtime and protect stakeholder confidence in analytics outputs
• Collaborate closely with data scientists analysts and domain experts to deliver curated data products that accelerate experimentation and support airline and enterprise decision making
• Drive continuous improvement of development workflows by refining version control branching strategies and deployment automation for Azure Databricks based solutions
• Document solution designs data models and operational procedures in a clear and comprehensive manner that supports knowledge sharing and onboarding of new team members
• Coordinate with security and compliance partners to implement data protection policies and ensure that all data solutions adhere to enterprise governance and regulatory requirements
• Optimize Spark jobs by tuning partitions caching and resource configurations to reduce processing time and infrastructure costs while maintaining predictable performance
• Mentor junior and mid level engineers by providing constructive feedback guidance on technical challenges and exposure to modern data engineering practices

Qualifications

• Possess extensive practical experience in PySpark development including writing efficient transformations handling complex joins and managing large scale distributed processing workloads
• Demonstrate strong proficiency in Python programming with focus on modular design error handling logging and integration with cloud native data services for robust pipeline implementations
• Bring hands on expertise with Azure Databricks including workspace configuration job orchestration secret management and integration with broader Azure data platforms such as Data Lake and Synapse
• Apply solid understanding of data warehousing concepts data modeling and ETL ELT patterns to design solutions that support analytics reporting and machine learning use cases
• Utilize knowledge of airline or travel industry data such as reservations operations or customer data as a nice to have capability that enhances domain centric analytics and insights
• Exhibit skill in collaborating within hybrid work models by using modern collaboration tools and clear communication practices to keep distributed stakeholders aligned during day shift operations
• Show capability to troubleshoot production incidents in an organized manner using logs metrics and root cause analysis practices that lead to durable preventive improvements.

Salary and Other Compensation:

The annual salary for this position is between $120-135Kdepending on experience and other qualifications of the successful candidate.

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:

• 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