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Salary
≈ $20k – $50k per year (Estimated)
Location
In office (Noida, Pune, Gurgaon)
Experience
3+ years exp

First seen by Alion on Sep 19, 2026.

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Job Title : BI Engineer - Data Engineering

Working Days : Monday to Friday.

Job Time : Day shift.

About the Role :

We are seeking an experienced BI Engineer to design and deliver scalable analytics solutions supporting Revenue Operations. This role partners with Sales, Marketing, Customer Success, Finance, and Product teams to build trusted data models, automate data pipelines, and deliver insights across the customer lifecycle from lead generation through retention, expansion, and churn reduction.

Job Role & Responsibility :

- Design and maintain scalable dimensional data models for enterprise reporting.

- Build and optimize ELT pipelines using SQL, dbt, Airflow, and Databricks.

- Develop dashboards and reporting solutions in Power BI.

- Integrate data from Revenue Operations platforms, including Salesforce, Marketo, Braze, Salesloft, Zuora, and NetSuite.

- Support analytics for pipeline, customer acquisition, MRR, ARR, renewals, upsell, churn, and Customer Success.

- Ensure data quality, governance, documentation, monitoring, and pipeline performance.

- Participate in code reviews, CI/CD, and continuous improvement initiatives.

- Evaluate and leverage AI capabilities such as Databricks Genie and AI Agents.

Skills :

- 5+ years of experience in BI, Analytics Engineering, or Data Engineering.

- Advanced SQL skills and experience with dimensional data modeling, including star and snowflake schemas.

- Hands-on experience with Databricks, dbt, Airflow, Power BI, and Git.

- Experience working with Revenue Operations systems, including Salesforce, Marketo, Braze, Salesloft, Zuora, and NetSuite.

- Exposure to Python and cloud data platforms such as Databricks, Snowflake, or Redshift.

- Strong analytical, problem solving, and communication skills.

Good to Have :

- Experience supporting Revenue Operations, Sales Operations, or Marketing Operations.

- Knowledge of SaaS metrics including MRR, ARR, pipeline conversion, renewal, customer health, and churn.

Skills

Business Intelligence, Dimensional Modeling, Data Modeling, ETL, SQL, Data Build Tool, Apache Airflow, Databricks, Dashboard Design, BI Reporting

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