Lead Data Engineer - Snowflake, Databricks

We are seeking a Lead Data Engineer with strong expertise in Azure Data Platform, Databricks, and Snowflake to drive the development of scalable cloud-native data solutions. This role will be responsible for building enterprise data products, modernizing legacy data platforms, and designing high-performance data processing frameworks. The ideal candidate will possess strong hands-on data engineering experience, cloud migration expertise, and the ability to lead delivery across complex enterprise data initiatives. This position requires a blend of architecture, engineering, and technical leadership capabilities.

In this role, you will:

• Design, develop, and deliver enterprise data products aligned with business and analytics roadmaps.
• Build and maintain cloud-native data platforms and pipelines leveraging Azure Synapse, Databricks, Snowflake, and Azure Data Factory.
• Define and execute data migration strategies from legacy on-premise environments to modern cloud-based data platforms.
• Develop and optimize scalable data processing frameworks for batch, streaming, and analytical workloads.
• Implement engineering best practices including CI/CD, automated testing, performance optimization, and operational monitoring.
• Design and support ETL/ELT workflows using tools such as SSIS, Informatica, ADF, and Spark-based frameworks.
• Collaborate with architects, analysts, product owners, and business stakeholders to translate requirements into technical solutions.
• Integrate enterprise data platforms with APIs, middleware technologies, and cloud-native services.
• Ensure data quality, governance, security, and compliance standards are incorporated into platform designs.
• Provide technical leadership, mentor team members, and support continuous improvement initiatives across data engineering practices.

• 8+ years of experience in Data Engineering, Data Platform Development, or Cloud Data Solutions.
• Strong hands-on expertise in Snowflake, including data modeling, performance optimization, and data warehouse architecture.
• Experience with Databricks and Apache Spark for large-scale data processing and transformation workloads.
• Strong knowledge of Azure Synapse Analytics, Azure Data Factory, Azure Data Lake Storage, Azure SQL Database, and related Azure data services.
• Experience building enterprise ETL/ELT frameworks using SSIS, Informatica, ADF, or equivalent technologies.
• Strong proficiency in SQL, Python, and big data processing frameworks.
• Understanding of streaming and middleware technologies such as Kafka.
• Experience integrating data platforms with APIs, API gateways, and enterprise applications.
• Familiarity with federated authentication and SSO technologies such as PingFederate, Okta, and SAML-based identity providers.
• Strong understanding of cloud migration, data modernization, CI/CD, automation, and DevOps practices.
• Excellent stakeholder management, problem-solving, and technical leadership skills.

The annual salary for this position is between $[115,500 - 135,500] depending 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: 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