JOB DESCRIPTION
Position/Title: | Senior Analytics Engineer |
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Department: | BI Platform Leadership |
Location: | Bangalore |
Shifts (if any) | 03:30 PM to 12:30 AM IST |
This is a job description for one of Aeries’ preferred partner - Quickbase. In this role, you will be working directly for our partner – as an employee of Aeries.
THE TOP 5 REASONS TO JOIN US
Quickbase Center of Excellence:
In 2023, Quickbase set up its Center of Excellence (CoE) in partnership with Aeries – to consolidate its global operations in Bangalore, India.
This CoE is focused on providing best practices, research, support, and training.
About Quickbase
Our no-code platform lets you easily create, connect, and customize enterprise applications that fix visibility and workflow gaps without replacing a single system.
Founded in 1999, Quickbase has since become the leading application platform for dynamic work. Used for complex project and portfolio management, the platform empowers more than 6,000 customers to see, connect, and control their processes and data all in one centralized location. Named an Inc’s Best Businesses of 2022, see for yourself why Quickbase is at the forefront of business- led innovation at Quickbase.com. Quickbase – All together now.
Read about us at: https://www.quickbase.com/
Job Description
We are hiring a Senior Analytics Engineer to shape and strengthen the analytics foundation that drives company performance.
This is a senior individual contributor role with meaningful influence. You will define modeling standards, evolve our BI platform, formalize enterprise metrics, and ensure data is structured to support confident decision making across the organization.
Success in this role requires more than technical execution. You will be expected to operate independently, bring structure to ambiguity, challenge unclear assumptions, and translate complex business problems into durable data solutions.
Key Responsibilities: BI Platform Leadership
Lead administration and continuous improvement of the Power BI environment
Define governance, security, modeling, and deployment standards
Design reusable, scalable datasets that promote metric consistency across teams
Improve platform performance, reliability, and cost efficiency
Analytics Modeling and Architecture
Architect and implement dimensional models in Snowflake using dbt
Build durable analytics layers aligned to core revenue and operational domains
Ensure strong alignment between warehouse structures and reporting logic
Embed testing, documentation, and performance optimization into standard engineering practice
Enterprise Metric Governance
Define and formalize KPI logic with clear business definitions and ownership
Maintain consistency of metrics across tools, systems, and reporting surfaces
Resolve conflicting definitions through structured analysis and stakeholder alignment
Strengthen transparency and trust in enterprise data assets
AI-Enabled Analytics
Treat AI as a core capability in modern analytics, leveraging it to deliver high-quality solutions with greater speed and rigor
Design data models and governance patterns that enable the organization to safely and effectively leverage AI with trusted data
Integrate AI into analytics workflows to accelerate modeling, validation, documentation, and insight generation
Apply disciplined judgment when evaluating AI-generated outputs, ensuring enterprise standards for accuracy and consistency
Establish practical guardrails for responsible AI usage across both engineering and business consumption
Cross-Functional Partnership
Translate complex and ambiguous business questions into scalable data solutions
Communicate technical tradeoffs clearly to both technical and business stakeholders
Introduce platform and process improvements and drive them through implementation
Influence data standards across the Data & Analytics function
What We Look For
Ability to operate independently in complex, evolving environments
Clear and structured communication
Strong analytical reasoning and disciplined problem solving
Ownership mindset with focus on measurable business outcomes
Willingness to challenge assumptions constructively
High standards for data quality, logical rigor, and validation
Requirements
- 6+ years of experience in analytics engineering or data engineering
- Deep experience with Power BI administration and dataset modeling
- Strong hands-on experience with Snowflake and dbt
- Advanced SQL with demonstrated performance tuning expertise
- Experience with Git-based workflows and CI/CD practices
- Proven experience designing and governing business metrics
- Preferred:
- Experience in SaaS or subscription-based businesses
- Experience working with global stakeholders
- Python for automation or platform tooling
WATCH OUR VIDEOS TO KNOW MORE ABOUT US!
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