About AI & Analytics: Artificial intelligence (AI) and the data it collects and analyzes will soon sit at the core of all intelligent, human-centric businesses. By decoding customer needs, preferences, and behaviors, our clients can understand exactly what services, products, and experiences their consumers need. Within AI & Analytics, we work to design the future—a future in which trial-and-error business decisions have been replaced by informed choices and data-supported strategies.
By applying AI and data science, we help leading companies to prototype, refine, validate, and scale their AI and analytics products and delivery models. Cognizant’s AIA practice takes insights that are buried in data and provides businesses a clear way to transform how they source, interpret and consume their information. Our clients need flexible data structures and a streamlined data architecture that quickly turns data resources into informative, meaningful intelligence.
*Please note, this role is not able to offer visa transfer or sponsorship now or in the future*
Job Summary
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.
What you need to have to be considered
· 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.
#LI-EF1
#CB
#Ind123
Applications will be accepted until 12 Aug 2026.
Salary and Other Compensation:
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
Über Cognizant
Cognizant (NASDAQ: CTSH) i ist ein Technologiedienstleister und Entwickler von KI-Lösungen. Wir schlagen die Brücke zwischen KI-Investitionen und echtem unternehmerischem Mehrwert, indem wir ganzheitliche Full-Stack-KI-Lösungen für unsere Kunden entwickeln. Mit unserer fundierten Branchen-, Prozess- und Engineering-Expertise integrieren wir die spezifischen Anforderungen von Unternehmen passgenau in Technologiesysteme. So entfalten wir das menschliche Potenzial, erzielen greifbare Ergebnisse und sichern globalen Unternehmen in einer sich rasant wandelnden Welt den entscheidenden Vorsprung. Erfahren Sie mehr unter cognizant.ai oder @cognizant.
Zusätzliche Informationen zur Beschäftigung
Die Vergütungsinformationen sind zum Zeitpunkt der Veröffentlichung dieser Stellenausschreibung korrekt. Cognizant behält sich das Recht vor, diese Informationen jederzeit unter Beachtung der geltenden gesetzlichen Bestimmungen zu ändern.
Bewerberinnen und Bewerber können verpflichtet sein, an Vorstellungsgesprächen persönlich oder per Videokonferenz teilzunehmen. Darüber hinaus kann es erforderlich sein, bei jedem Gespräch einen gültigen staatlichen Lichtbildausweis vorzulegen.
Cognizant ist ein Arbeitgeber mit Chancengleichheit. Ihre Bewerbung und Kandidatur werden nicht aufgrund von Rasse, Hautfarbe, Geschlecht, Religion, Glaubensbekenntnis, sexueller Orientierung, Geschlechtsidentität, nationaler Herkunft, Behinderung, genetischen Informationen, Schwangerschaft, Veteranenstatus oder sonstiger durch bundes‑, landes‑ oder kommunalrechtliche Vorschriften geschützter Merkmale berücksichtigt oder abgelehnt.







