Pay: 10-20 lakh per year
Location: Hyderabad 3x a week
MUST HAVES:
- 5+ years of experience in data engineering, analytics, or related fields; a proven ability to build and evolve analytics solutions.
- Fluency in SQL, dbt, and ideally Python; strong understanding of modern data tooling and engineering principles.
- Experience working with Databricks (on AWS preferred).
- Curiosity about Generative AI, data products, and how emerging tools can drivebusiness value.
- Demonstrated ability to work across business domains (marketing, product, finance,
- sales, customer success, etc.).
- Experience with cloud-native data sources like Salesforce or NetSuite.
- Clear, compelling communicationboth technical and business-facing.
- A product mindset and a passion for continuous learning
PLUSSES:
- Growth mindset/someone who is keeping themselves well versed.
- Experience with AI
Day to Day:
This Analytics Engineer will bridge the gap between business and technical teams by creating trusted, scalable, and efficient data models and products. A successful Analytics Engineer can combine his/her technical expertise with business acumen to deliver actionable insights. They will be working collaboratively and independently. Currently the team is working on Sales efficiency projects and financial PowerBI/data modeling projects. They utilize AWS and Databricks in their current environment as well as DBT, Domo, Python, PowerBI, and SQL. This individual must be able to do every aspect of the ETL process as this is a small team of 5 people and everyone jumps in where needed on projects. You will be expected to go into the Hyderabad office three times a week.
Responsibilities
As a team member responsible for helping to blend business-critical data needs with technical solutions, the Analytics Engineer role requires acumen in both domains.
- Collect business requirements and design highly optimized data models.
- Identify performance metrics definition and automation opportunities.
- Build trust through data conversion to data stories for internal and external consumption.
- Serve as the subject matter expert for the Enterprise Data Model
- Design, develop, and extend dbt code to enhance the Enterprise Dimensional Model.
- Create and maintain architecture and systems documentation.
- Provide cross-team support for CRM and Marketing teams.
- Assist with complex data analysis tasks.
- Implement the DataOps philosophy in everything you do.
- Create enterprise-grade reporting/data visualization solutions.
