Job Role: Data Engineer

Role Overview and Expected Deliverables

The engineer will design, build and operate scalable, secure and analytics‑ready data pipelines and models across GCP BigQuery and AWS, delivering:
Airflow‑orchestrated data workflows and automations.
DBT Cloud transformations, testing frameworks and environment governance.
Robust CI/CD and Infrastructure as Code (IaC) deployments (GitHub Actions, Bitbucket, Bamboo, Terraform or CloudFormation).
Performance optimisation across data pipelines, SQL, BigQuery and AWS data services.
High‑quality technical documentation, production support, incident response and handover to internal teams.
Close collaboration with cross‑functional stakeholders including analytics, product and platform engineering.

Core Technical Requirements

Cloud & Platform Engineering:
Solid proficiency across AWS and GCP.
On AWS: IAM roles and policies, Lambda, S3, RDS, Redshift.
On GCP: BigQuery, workload optimisation, cost management.

Data Engineering Tooling:




Hands‑on experience building data pipelines for data warehouse environments.
Solid SQL capability including analytical and window functions.
Advanced dbt Cloud experience (models, SCDs, tests, macros, release management).
Airflow workflow design including idempotency, backfills and monitoring.

DevOps, CI/CD & IaC:
Experience with CI/CD (GitHub, Bitbucket, GitHub Actions, Bamboo).
Infrastructure as Code using Terraform or CloudFormation.
Familiarity with data quality frameworks and automated testing of pipelines.

Programming & Modelling:
Proficiency in Python.
Robust data modelling expertise: facts/dimensions, SCD patterns, performance optimisation.

Security, Data Governance & Operational Resilience:
Solid grounding in cloud security best practices and least‑privilege IAM.
Understanding of data access controls, regulated environments and governance expectations.

Delivery Approach & Ways of Working
Experience working within Agile

📌 Data Engineer Delhi
🏢 Arminus
📍 Delhi