Job description

About the role As a Senior Data Engineer - Snowflake and Lakehouse , you will make an impact by designing, building, and optimizing scalable data solutions that power analytics, reporting, and data-driven decision-making across the enterprise. You will be a valued member of the data engineering team and work collaboratively with client technology leads, analytics teams, data scientists, and platform engineers to deliver modern Lakehouse capabilities using Snowflake and the modern data stack. In this role, you will: • Design and build scalable batch and near real-time data ingestion pipelines using Snowpipe and Snowpipe Streaming. • Develop and maintain robust data transformation frameworks and curated data models using dbt and industry best practices. • Build and optimize data processing solutions using Snowpark (Python and Spark) to support advanced transformations and machine learning use cases. • Implement and manage Dynamic Tables, Snowflake Tasks, and workflow orchestration to automate and streamline data operations. • Design and maintain Apache Iceberg-based Lakehouse architectures that enable open, interoperable, and high-performing data platforms. • Integrate Kafka event streams and CDC data sources into Snowflake to support scalable real-time analytics. • Monitor data platform health, optimize warehouse utilization, and implement cost and performance controls. • Establish data quality standards, schema validation processes, testing frameworks, and operational best practices. • Partner with cross-functional stakeholders to define data contracts, governance standards, and Lakehouse architecture guidelines. • Create and maintain technical documentation, architecture diagrams, data lineage artifacts, and operational runbooks. Work model At Cognizant, we strive to provide flexibility wherever possible, and we are here to support a healthy work-life balance through our various well-being programs. Based on this role's business requirements, this is an onsite position requiring 5 days per week in a client office in either Phoenix, Arizona or Johnston, Rhode Island . The working arrangements for this role are accurate as of the date of posting. This may change based on the project you're engaged in, as well as business and client requirements. Rest assured; we will always be clear about role expectations. What you need to have to be considered • Minimum 5 years of hands-on experience delivering data engineering solutions with Snowflake in enterprise environments. • Strong experience with Snowflake platform capabilities including virtual warehouses, security roles, tasks, performance tuning, and operational management. • Proven experience implementing batch and real-time ingestion solutions using Snowpipe and Snowpipe Streaming. • Hands-on experience with dbt for data transformations, testing, documentation, and version-controlled development practices. • Strong experience with Snowpark using Python and Spark for scalable data processing and transformation workloads. • Experience integrating Kafka event streams and/or Change Data Capture (CDC) pipelines with Snowflake. • Hands-on experience with AWS services such as S3, IAM, Glue, and Lambda supporting cloud-based data platforms. • Advanced SQL skills and strong understanding of data modeling, dimensional design, and Lakehouse architecture principles. • Experience with Dynamic Tables, workflow orchestration, and automated pipeline management. • Experience using Git-based source control and CI/CD practices for data engineering solutions. • Strong understanding of data governance, security, access controls, and cost optimization within Snowflake environments. These will help you stand out • Experience developing large-scale processing solutions using Java Spark. • Familiarity with Interactive Tables or low-latency data serving frameworks within Snowflake. • Experience with workflow orchestration platforms such as Apache Airflow. • Experience leading or supporting migrations from traditional data warehouse environments to modern Lakehouse architectures. • Snowflake certifications such as SnowPro Core or SnowPro Advanced. We're excited to meet people who share our mission and can make an impact in a variety of ways. Don't hesitate to apply, even if you only meet the minimum requirements listed. Think about your transferable experiences and unique skills that make you stand out as someone who can bring new and exciting things to this role. *Please note, this role is not able to offer visa transfer or sponsorship now or in the future* Salary and Other Compensation: Applications will be accepted until October 04, 2025 The annual salary for this position is between $ 100,000 - $ 115,000 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: 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 law. About Cognizant: Cognizant (Nasdaq: CTSH) is an AI Builder and technology services provider, bridging the gap between AI investment and enterprise value by building full-stack AI solutions for our clients. Our deep industry, process and engineering expertise enables us to build an organization’s unique context into technology systems that amplify human potential, drive tangible outcomes and keep global enterprises ahead in a fast-changing world. See how at cognizant.ai or @cognizant. Additional employment information Compensation information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law. Applicants may be required to attend interviews in person or by video conference. In addition, candidates may be required to present their current state or government issued ID during each interview. Cognizant is an equal opportunity employer. Your application and candidacy will not be considered based on race, color, sex, religion, creed, sexual orientation, gender identity, national origin, disability, genetic information, pregnancy, veteran status or any other characteristic protected by federal, state or local laws. If you have a disability that requires reasonable accommodation to search for a job opening or submit an application, please email CareersNA2@cognizant.com for roles based in the Americas or CareersIndia2@cognizant.com for roles based in India.

Requirements

Must-haves

Design and build scalable batch and near real-time data ingestion pipelines using Snowpipe and Snowpipe Streaming.
Develop and maintain robust data transformation frameworks and curated data models using dbt and industry best practices.
Build and optimize data processing solutions using Snowpark (Python and Spark) to support advanced transformations and machine learning use cases.
Implement and manage Dynamic Tables, Snowflake Tasks, and workflow orchestration to automate and streamline data operations.
Design and maintain Apache Iceberg-based Lakehouse architectures that enable open, interoperable, and high-performing data platforms.
Integrate Kafka event streams and CDC data sources into Snowflake to support scalable real-time analytics.
Monitor data platform health, optimize warehouse utilization, and implement cost and performance controls.
Establish data quality standards, schema validation processes, testing frameworks, and operational best practices.
Partner with cross-functional stakeholders to define data contracts, governance standards, and Lakehouse architecture guidelines.
Create and maintain technical documentation, architecture diagrams, data lineage artifacts, and operational runbooks.
What you need to have to be considered
Minimum 5 years of hands-on experience delivering data engineering solutions with Snowflake in enterprise environments.
Strong experience with Snowflake platform capabilities including virtual warehouses, security roles, tasks, performance tuning, and operational management.
Proven experience implementing batch and real-time ingestion solutions using Snowpipe and Snowpipe Streaming.
Hands-on experience with dbt for data transformations, testing, documentation, and version-controlled development practices.
Strong experience with Snowpark using Python and Spark for scalable data processing and transformation workloads.
Experience integrating Kafka event streams and/or Change Data Capture (CDC) pipelines with Snowflake.
Hands-on experience with AWS services such as S3, IAM, Glue, and Lambda supporting cloud-based data platforms.
Advanced SQL skills and strong understanding of data modeling, dimensional design, and Lakehouse architecture principles.
Experience with Dynamic Tables, workflow orchestration, and automated pipeline management.
Experience using Git-based source control and CI/CD practices for data engineering solutions.
Strong understanding of data governance, security, access controls, and cost optimization within Snowflake environments.
These will help you stand out
Experience developing large-scale processing solutions using Java Spark.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

pythonmachine learningrestawssqlci/cdjavaai

Platform: cognizant
Effort: medium

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Paid Time Off

Parental Leave