About the role
structured by ORIExperience: 1-3 years of experience. Your Role and Responsibilities: We??re looking for a BI Developer / Analytics Engineer to accelerate analytics capabilities across Finance, Field Operations, and adjacent Go-to-Market (GTM) stakeholders, including Sales, Customer Success, and partner-facing teams.
What you will do
- Partner with stakeholders across Field Operations, Sales, Customer Success, and related teams to understand business processes, define metrics, and translate requirements into scalable analytics solutions.
- Build and maintain trusted datasets, reusable data models, and semantic definitions using SQL-first analytics engineering practices on top of modern cloud data platforms.
- Develop and maintain production-grade ELT workflows and data transformations using technologies such as BigQuery, dbt, Airflow, and Git-based development practices.
- Deliver analytical insights for Monthly Business Reviews (MBRs), Quarterly Business Reviews (QBRs), and executive reporting through deep-dive analyses that proactively identify data, reporting, and process gaps.
- Design and deliver high-quality dashboards and self-service analytics experiences using tools such as Tableau, Hex, Looker, Power BI, and emerging semantic-layer technologies.
What they are looking for
- 3+ years of experience in Business Intelligence, Analytics, or Analytics Engineering roles, with strong hands-on expertise in data modeling, SQL development, analysis, and dashboard/report delivery.
- Strong sense of ownership and proactive communication skills, with the ability to drive effective collaboration across multiple time zones and stakeholder groups.
- Expert SQL skills and experience working with modern cloud data warehouses such as BigQuery, Snowflake, or Databricks.
- Proven experience building scalable semantic models, trusted datasets, and curated reporting layers that improve self-service analytics adoption and metric consistency.
- Experience with BI and analytics platforms such as Tableau, Hex, Looker, Power BI, or similar tools, with the ability to select the appropriate solution for a given business use case.
- Strong stakeholder management, communication, and problem-solving skills, with the ability to translate ambiguous business requirements into well-governed analytical solutions.
- Ability to work cross-functionally with technical and non-technical stakeholders to drive measurable business outcomes.
Nice to have
- Experience with dbt and workflow orchestration tools such as Airflow, Dagster, or Prefect is strongly preferred.
- Experience in a B2B SaaS environment, particularly supporting GTM, customer success, product usage, revenue operations, or financial analytics functions.
- Python programming experience, including developing reusable data functions, automation workflows, and API-integrated solutions.
- Experience working with CRM and business systems data, including Salesforce, finance systems, product telemetry, customer data, and account-level analytics.
- Experience leading or supporting business intelligence, data warehouse, or cloud analytics platform migrations, including implementation of associated best practices.
- Curiosity and enthusiasm for AI-assisted analytics, conversational analytics, and the future of governed self-service data experiences.
- Familiarity with analytics governance practices, including role-based access control (RBAC), sensitive data management, metric standardization, semantic layer design, and trusted dataset certification.
- Experience with data quality and observability tooling, warehouse performance optimization, and cost-efficient data platform design.
Full posting text
Experience: 1-3 years of experience.
Your Role and Responsibilities: We??re looking for a BI Developer / Analytics Engineer to accelerate analytics capabilities across Finance, Field Operations, and adjacent Go-to-Market (GTM) stakeholders, including Sales, Customer Success, and partner-facing teams.
This role is ideal for someone who combines strong business intuition with modern analytics engineering expertise. You will partner closely with business stakeholders, Data Scientists, and Data Engineers to translate business questions into trusted datasets, production-grade transformations, semantic definitions, and high-quality dashboards and self-service analytics experiences.
Successful candidates will bring strong SQL and data modeling skills, a product mindset for analytics, and the ability to balance speed with reliability, governance, and scale.
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What You''ll Do
- Partner with stakeholders across Field Operations, Sales, Customer Success, and related teams to understand business processes, define metrics, and translate requirements into scalable analytics solutions.
- Build and maintain trusted datasets, reusable data models, and semantic definitions using SQL-first analytics engineering practices on top of modern cloud data platforms.
- Develop and maintain production-grade ELT workflows and data transformations using technologies such as BigQuery, dbt, Airflow, and Git-based development practices.
- Deliver analytical insights for Monthly Business Reviews (MBRs), Quarterly Business Reviews (QBRs), and executive reporting through deep-dive analyses that proactively identify data, reporting, and process gaps.
- Design and deliver high-quality dashboards and self-service analytics experiences using tools such as Tableau, Hex, Looker, Power BI, and emerging semantic-layer technologies.
- Improve data quality, governance, and observability by driving documentation, testing, lineage, access controls, and root-cause analysis in partnership with Data Engineering and platform teams.
- Collaborate with Data Scientists and Data Engineers to ensure consistent metric definitions and scalable reporting solutions across the business.
- Champion analytics best practices that enable trusted, governed, and scalable self-service reporting.
Required Education:
Bachelor''s Degree
Preferred education
Master''s Degree
Required Technical and Professional Expertise:
- 3+ years of experience in Business Intelligence, Analytics, or Analytics Engineering roles, with strong hands-on expertise in data modeling, SQL development, analysis, and dashboard/report delivery.
- Strong sense of ownership and proactive communication skills, with the ability to drive effective collaboration across multiple time zones and stakeholder groups.
- Expert SQL skills and experience working with modern cloud data warehouses such as BigQuery, Snowflake, or Databricks.
- Experience with dbt and workflow orchestration tools such as Airflow, Dagster, or Prefect is strongly preferred.
- Proven experience building scalable semantic models, trusted datasets, and curated reporting layers that improve self-service analytics adoption and metric consistency.
- Experience with BI and analytics platforms such as Tableau, Hex, Looker, Power BI, or similar tools, with the ability to select the appropriate solution for a given business use case.
- Strong stakeholder management, communication, and problem-solving skills, with the ability to translate ambiguous business requirements into well-governed analytical solutions.
- Ability to work cross-functionally with technical and non-technical stakeholders to drive measurable business outcomes.
Preferred Technical and Professional Experience:
- Experience in a B2B SaaS environment, particularly supporting GTM, customer success, product usage, revenue operations, or financial analytics functions.
- Python programming experience, including developing reusable data functions, automation workflows, and API-integrated solutions.
- Experience working with CRM and business systems data, including Salesforce, finance systems, product telemetry, customer data, and account-level analytics.
- Experience leading or supporting business intelligence, data warehouse, or cloud analytics platform migrations, including implementation of associated best practices.
- Curiosity and enthusiasm for AI-assisted analytics, conversational analytics, and the future of governed self-service data experiences.
- Familiarity with analytics governance practices, including role-based access control (RBAC), sensitive data management, metric standardization, semantic layer design, and trusted dataset certification.
- Experience with data quality and observability tooling, warehouse performance optimization, and cost-efficient data platform design.
- Knowledge of modern data stack architectures and best practices for scalable analytics engineering.
Years of Experience: 1 - 3
Key skills: Ai, Airflow, Business Intelligence, Automation, Customer Success, Bigquery, Analytics Platforms, Analytics, Cloud Data, Business Requirements, Cloud Analytics, Communication Skills, Confluent, B2B, Cloud, Business Systems, Bi Developer, Crm.
Role: Analytics Consultant
Industry Type: IT Services & Consulting
Department: Data Science & Analytics
Employment Type: Full Time, Permanent
Role Category: Business Intelligence & Analytics
Education: UG: Any Graduate
Education: PG: Any Postgraduate