Sr. Data Engineer - Snowflake and Lakehouse

Cognizant; Phoenix (AZ); On-site; USD 100,000 - 115,000; Full time

Benefits offered by this job

Medical/Dental/Vision/Life Insurance

Paid holidays + PTO

401(k) plan and contributions

Long-term/Short-term Disability

Paid Parental Leave

Employee Stock Purchase Plan

Job summary

Cognizant is seeking a Senior Data Engineer to design, build, and optimize scalable data solutions on Snowflake Lakehouse. You will collaborate with analytics and engineering teams to deliver modern data platforms, incorporating Snowflake, Iceberg, Kafka streams, and CDC pipelines.

You will implement data contracts, governance standards, and operate pipelines with robust testing, quality controls, and cost optimization in a client-focused environment in the United States.

Qualifications

• 5+ years of hands-on data engineering experience with Snowflake in enterprise settings.
• Strong knowledge of Snowflake features: virtual warehouses, tasks, security, performance.
• Proven experience building batch and real-time ingestion with Snowpipe pipelines.
• Hands-on dbt for transformations, testing, and version control.
• Experience with Snowpark (Python/Spark) for scalable processing.
• Experience integrating Kafka or CDC pipelines with Snowflake.
• Experience with AWS services (S3, IAM, Glue, Lambda) for cloud data platforms.
• Advanced SQL, data modeling, dimensional design, and Lakehouse principles.
• Familiarity with dynamic tables, orchestration, and CI/CD for data.

Responsibilities

• Design and implement scalable data ingestion pipelines using Snowpipe and Snowpipe Streaming.
• Develop and maintain robust data transformation frameworks with dbt.
• Build Lakehouse architectures with Snowflake, Iceberg, and related tooling.
• Integrate Kafka streams and CDC sources for real-time analytics.
• Optimize warehouse usage and implement cost/performance controls.
• Establish data quality, schema validation, and testing frameworks.
• Collaborate with stakeholders to define data contracts and governance.
• Create architecture diagrams, data lineage, and runbooks.
• Lead or support migrations to modern Lakehouse architectures.

Skills

Snowflake

Snowpipe

Snowpark

dbt

Kafka

Spark

Python

AWS

Git

Airflow

SQL

Data modeling

CI/CD

Tools

Snowflake

Snowpipe

Snowpark

dbt

Kafka

Python

Spark

Airflow

Git

S3

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. 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 September 13, 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:

• 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.