Mid Data Engineer

Mid Data Engineer

Mid Data Engineer (#006fu00000QeELXAA3-11)

Responsibilities

• Design, build, and operate scalable ETL/ELT pipelines that ingest AI Assistant, DevOps, API, database, event, and log data into Snowflake.
• Build and maintain dbt data models, tests, and documentation while designing Snowflake staging, core, and mart layers and optimizing performance and cost.
• Design and manage MongoDB collections, schemas, indexes, aggregation pipelines, and change streams, integrating MongoDB with the analytics layer.
• Implement data observability, quality checks, lineage, security controls, monitoring, CI/CD, and production operations while partnering with analytics and product teams to deliver reliable data products.

Requirements

• Snowflake, MongoDB, dbt, ETL/ELT, Data Modeling, SQL, CI/CD, Data Observability, Power BI, Tableau, AI-Assisted Development

Hybrid – 2–3 days per week on-site

• with the following skill set.
• Hands-on experience designing and developing scalable ETL/ELT data pipelines.
• Strong experience with Snowflake, including data modeling, dimensional/star schemas, query tuning, and performance optimization.
• Hands-on experience with dbt for data modeling, testing, and documentation.
• Experience working with MongoDB, including collections, schemas, indexes, aggregation pipelines, and change streams.
• Experience integrating data from APIs, databases, event sources, logs, and DevOps platforms.
• Experience with data visualization tools or libraries such as Power BI or Tableau.
• Knowledge of data observability, quality validation, lineage tracking, monitoring, and alerting.
• Experience with CI/CD, Git, infrastructure as code, and Dev/QA/Prod environments.
• Knowledge of data security practices, including RBAC, masking, encryption, and audit controls.
• Experience using generative AI coding assistants such as GitHub Copilot, Codex, Claude Code, or Cursor, with the ability to validate AI-generated outputs through rigorous testing.

Preferred

• Experience working with data generated by AI development assistants such as Cursor, Codex, Claude, Copilot, or Devin.
• Familiarity with DevOps and engineering data sources such as Jenkins, SonarQube, Git, and Jira.
• Experience supporting incident triage, root cause analysis, and runbook creation for data platforms.
• Experience translating business and delivery requirements into data products, analytics, and dashboards.

We at Coforge are hiring

Posted On

22-10-2026

At Coforge, we hire professionals based solely on their skills and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality.