Role Overview:
We are looking for a hands-on dbt Data Engineer / Developer to build, test, and maintain scalable ELT transformation pipelines using dbt, SQL, Snowflake, and modern cloud data platforms.
· Design, develop, and maintain dbt models for staging, intermediate, and mart layers.
· Build ELT pipelines using SQL, dbt, and Snowflake, including staging, transformation, and data mart layers; exposure to Databricks, BigQuery, Redshift, or Azure Synapse is an added advantage.
· Implement dbt tests, documentation, source freshness checks, snapshots, and reusable macros.
· Optimize SQL queries and dbt models for performance, reliability, and maintainability.
· Work with analysts, business users, and senior data engineers to translate requirements into data models and transformation logic.
· Support Git-based development, pull requests, code reviews, CI/CD deployments, and environment management.
· Exposure to legacy data warehouse migration or modernization initiatives, preferably involving Teradata to Snowflake migration, including support for SQL conversion, data validation, reconciliation, and defect fixes.
· Troubleshoot pipeline failures, data quality issues, and production defects in collaboration with platform and support teams.
Required Skills and Experience:
· Strong experience in data engineering, ETL/ELT development, analytics engineering, or data warehousing.
· Strong hands-on experience with dbt Core or dbt Cloud.
· Advanced SQL skills with experience in complex transformations and performance tuning.
· Good understanding of dimensional modelling, star schema, data marts, and warehouse concepts.
· Hands-on experience with Snowflake, including SQL development, warehouse usage, schemas, tables, views, access roles, and performance-aware query design.
· Good understanding of Snowflake objects such as databases, schemas, virtual warehouses, stages, file formats, streams, tasks, and secure views.
· Good understanding or hands-on exposure to Teradata concepts, SQL, data warehouse objects, BTEQ scripts, stored procedures, views, and migration activities from Teradata to Snowflake.
· Experience supporting migration testing, source-to-target validation, record count checks, data quality checks, and comparison of migrated data between Teradata and Snowflake.
· Good-to-have exposure to mainframe data sources, including COBOL copybooks, VSAM files, DB2 on z/OS, JCL, batch files, flat files, and mainframe-to-cloud data extraction patterns.
· Experience with Git, branching strategies, pull requests, and code review processes.
· Strong analytical, problem-solving, communication, and team collaboration skills.
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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 [email protected] with your request and contact information.
