Data Engineer
Job Summary
We, at Coforge, are seeking an experienced Data Engineer with strong hands-on expertise in dbt, Argo Workflows, and Kubernetes-based data platforms. The ideal candidate will design, build, and operate scalable, reliable data pipelines that power analytics, reporting, and downstream data consumers in a cloud-native environment.
Key Responsibilities
- Design, develop, and maintain scalable ELT pipelines using dbt for data transformation and modeling.
- Orchestrate and manage data workflows using Argo Workflows in a Kubernetes environment.
- Build and operate cloud-native data pipelines running on Kubernetes, ensuring reliability, scalability, and observability.
- Collaborate with analytics, data science, and business teams to translate data requirements into well-modeled datasets.
- Implement data quality checks, testing, and monitoring within dbt and orchestration layers.
- Optimize performance of data transformations, queries, and workflow executions.
- Ensure data security, governance, and compliance standards are followed.
- Participate in code reviews, documentation, and knowledge sharing across the team.
- Troubleshoot and resolve data pipeline failures, performance bottlenecks, and infrastructure issues.
- Support CI/CD practices for data pipelines and dbt projects.
Required Skills & Qualifications
- 3–8 years of experience in data engineering or related roles.
- Advanced SQL skills and proficiency in Python and/or Shell scripting.
- Experience with cloud data platforms and storage (e.g., AWS S3 - Redshift, Snowflake, or similar).
- Exposure to large data sets.
- Strong hands-on expertise with DBT (Data Build Tool) – ETL Transformation - for data transformation, testing, and modeling.
- Proven experience orchestrating workflows using Argo Workflows (orchestration for scheduling – can be cross trained from airflow)
- Solid working knowledge of Kubernetes, including pod execution, resource management, and debugging.
- Familiarity with CI/CD pipelines, Git-based version control, and infrastructure-as-code concepts.
- Strong understanding of data warehousing principles, dimensional modeling, and ELT architectures.
- Excellent problem-solving skills, attention to detail, and ownership mindset.
- Strong communication skills and ability to collaborate across cross-functional teams.
- Experience running dbt on Kubernetes using Argo or similar orchestrators.
- Exposure to cloud-native observability tools (logging, monitoring, alerting).
- Experience with modern data warehouses (Snowflake, BigQuery, Redshift).
- Knowledge of data governance, access control, and metadata management.
- Familiarity with visualization tools such as Tableau, Power BI, or Looker.
- Cloud certifications (AWS, GCP, or Kubernetes) are a plus.
