Data Engineer - Snowflake & Analytics Engineering- Ahmedabad
Actively Reviewing the ApplicationsHYrEzy Tech Solutions
India, Ahmedabad, Gujarat
Full-Time
On-site
INR 12–16 LPA
Posted 3 weeks ago
•
Apply by May 3, 2026
Job Description
Role: Data Engineer (Snowflake & Analytics Engineering)
In an era where "Data is the new Oil," our firm acts as the refinery. We don't just move bytes; we engineer intelligence. As a Data Engineer, you are joining a high-performance consulting squad dedicated to transforming messy, fragmented data into high-fidelity, fact-based assets.
You will be the architect of ELT pipelines that empower global organizations to make multi-million dollar decisions with absolute confidence.
The Technical Sovereignty (What You Own)
- Core Mission : Architecting the Modern Data Stack
- Primary Engine : Snowflake + dbt / Matillion
- Location : Ahmedabad
- Availability : Immediate to 30 Days (Critical Path)
- Experience: 3 to 5 Years
In an era where "Data is the new Oil," our firm acts as the refinery. We don't just move bytes; we engineer intelligence. As a Data Engineer, you are joining a high-performance consulting squad dedicated to transforming messy, fragmented data into high-fidelity, fact-based assets.
You will be the architect of ELT pipelines that empower global organizations to make multi-million dollar decisions with absolute confidence.
The Technical Sovereignty (What You Own)
- The Modern ELT Stack :
- Snowflake Mastery : You are the custodian of the cloud data warehouse. You will optimize warehouse sizing, implement RBAC security, and perform deep-dive query profiling to ensure sub-second response times.
- Transformation Logic (dbt/Matillion) : You will move away from brittle ETL. You will build modular, version-controlled transformations using dbt or Matillion (DPC), following the Medallion (Bronze/Silver/Gold) architecture.
- Hybrid Integration : While we lead with the cloud, you will bridge the gap with legacy systems using SSIS, ensuring a 360-degree data view.
- Orchestration & Cloud Ecosystem :
- Azure Integration : You will leverage Azure Data Factory and Data Lake Storage to orchestrate complex data movements from APIs, flat files, and on-premise databases.
- Analytics Engineering : You will treat data as codeapplying CI/CD, Git-based workflows, and automated testing (dbt tests) to ensure data quality is never compromised.
- Experience : 3- 5 years in Data Engineering. You must have "survived" at least 2 years of hands-on Snowflake and dbt/Matillion deployment in production.
- Expert-level SQL (The foundation of everything we do).
- Proficient Python (For automation and notebook-driven engineering).
- Deep understanding of Kimball/Dimensional Modeling.
- The Consultant Mindset : You are comfortable with ambiguity, can handle high-pressure client demos, and can explain a "partitioning strategy" to a non-technical stakeholder.
- Pipeline Reliability : Ensuring 99% uptime of scheduled dbt/Matillion jobs
- Performance Optimization : Reducing Snowflake credit consumption through efficient SQL and clustering strategies.
- Data Quality : Implementing automated tests that catch "bad data" before it reaches the client-facing dashboards.
- The "Joining Bonus" Edge : For candidates who can hit the ground running immediately, we offer a ?1 Lakh joining bonus.
- Consulting Variety : You won't be bored. You will solve different problems for different global clients every quarter.
- Office Synergy : This is a 5-day-a-week collaborative office environment in Ahmedabad, designed for rapid peer-to-peer learning.
Required Skills
Engineering
Git
Automation
Python
SQL
Snowflake
Azure
Data Lake
ETL
SSIS
KPIs
Data Engineering
CI/CD
Automated Testing
Testing
Credit
Analytics
Data quality
On-premise
DBT
Profiling
Orchestration
Performance optimization
Consulting
Modeling
Dimensional modeling
RBAC
Legacy systems
Files
Clustering
Data warehouse
Strategic context
Dashboards
Factory
Analytics Engineering
Automated tests
Cloud Data
Storage
Dimensional
ELT
Synergy
Azure Data Factory
Partitioning
Matillion
Sizing
Data Factory
Modern Data Stack
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