Description
- Senior Analytics Engineer (Data Engineering / Analytics Engineering)
- Location : Chandigarh IT Park (Work From Office)
- Experience : 6 to 10+ Years
AcmeMinds Private Limited is a digital product engineering and technology consulting firm that partners with startups and enterprises to design, build, and scale innovative digital solutions. Our expertise spans engineering, design, and AI, delivering services such as enterprise application development, mobile and web apps, UI/UX design, AI & data engineering, and more.
This is a full-time role based in Chandigarh. We are looking for a highly skilled and hands-on Senior Analytics Engineer to own the design, development, and evolution of our analytics data foundation.
In this role, you will transform raw data into trusted, scalable, and analytics-ready datasets that power reporting, experimentation, and business decision-making across the organization.
This is a senior-level, high-ownership role requiring strong technical expertise, problem-solving capability, and the ability to work independently while collaborating closely with analytics, product, engineering, and business teams.
This role focuses on analytics engineering, data modeling, and business data enablement not on traditional backend application development.
Why This Role Matters
The Senior Analytics Engineer plays a critical role in ensuring data is trustworthy, scalable, and usable. Your work will directly impact how teams understand performance, make decisions, and move the business forward.
Build & Maintain Analytics Foundations
- Design, build, and maintain analytics-ready data models using dbt, following best practices for modularity, testing, and documentation
- Develop and optimize SQL transformations in cloud data warehouses to support reliable reporting and analysis
Engineering Excellence
- Produce clean, readable, and testable code that adheres to analytics engineering standards
- Implement and maintain data tests, freshness checks, and documentation to ensure data quality and trust
- Design reusable components and patterns that enable scale and long-term maintainability
- Continuously identify and drive improvements to existing systems, pipelines, and workflows
Problem Solving & Technical Ownership
- Independently break down ambiguous or complex problems into clear technical solutions
- Anticipate risks, tradeoffs, and downstream impacts when making architectural and modeling decisions
- Balance speed of delivery with long-term scalability and maintainability
- Take ownership from problem definition through implementation, validation, and rollout
Enable Analytics & BI
- Partner with analytics and business teams to translate questions into robust data models
- Support BI tools and reporting workflows; experience with modern BI platforms required
- Looker experience is a strong bonus, particularly with LookML modeling and semantic layers
Collaboration & Leadership
- Work cross-functionally with product, engineering, analytics, and business stakeholders
- Clearly communicate technical decisions, tradeoffs, and data concepts to non-technical audiences
- Contribute to standards, documentation, and shared best practices across the data team
Experience & Technical Skills
- 6+ years of experience in analytics engineering, data engineering, or a related data role
- Strong proficiency with dbt (models, tests, documentation, macros)
- Advanced MYSQL skills with experience working in modern analytical databases (e.g., Redshift or similar)
- Experience supporting analytics and reporting via BI tools (Tableau, Power BI, Mode, etc.); Looker strongly preferred
- Familiarity with version control, CI/CD workflows, and production data environments
- Experience working in cloud-based data ecosystems
Senior-Level Expectations
- Demonstrated ability to operate independently with minimal direction
- Proactive in identifying gaps and opportunities to improve systems and processes
- Detail-oriented with a strong sense of ownership and accountability
- Able to influence technical direction without formal authority
Nice To Have
- Experience defining analytics engineering standards or data modeling conventions
- Experience designing scalable metrics layers or semantic models
- Prior exposure to data governance, lineage, or observability tooling
(ref:hirist.tech)
