Lead Data Engineer – Snowflake, Databricks

Cognizant is a leading company in the digital industry, seeking a Lead Data Engineer with expertise in Azure Data Platform, Databricks, and Snowflake. The role involves driving the development of scalable cloud-native data solutions and modernizing legacy data platforms while providing technical leadership and mentoring team members.

Responsibilities:

• 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

Requirements:

• 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