Data Engineer (Industrial ETL & Infrastructure)
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Monthly Salary:
Posted on:
2 hours ago
Vacancies:
5 Vacancies
Job Summary
Data Engineer (Industrial ETL & Infrastructure)
Location: Bangalore (Work from Office) Experience: 0 - 4 Years Type: Full-time
The Business Context
We are the #1 Carbon Accounting Platform for Industrial Manufacturing. We are on a mission to reduce 50% of global industrial emissions by 2030. To do this we must ingest and process billions of data points from steel plants and supply chains across the globe. We are a team of ex-McKinsey Partners building the tech backbone of the Net-Zero movement.
The Role
We are looking for a Data Engineer who loves building robust scalable data architectures. You will be responsible for designing the systems that ingest clean and store industrial data so our AI can turn it into carbon insights.
Key Responsibilities
Pipeline Construction: Design and maintain high-performance ETL/ELT pipelines to ingest data from diverse industrial sources (SAP IoT Sensors Excel SQL).
Data Lake Management: Architect and manage our data lake/warehouse infrastructure on AWS (Redshift/S3) or Azure.
Schema Design: Develop complex SQL schemas and optimize query performance for real-time sustainability dashboards.
Data Quality & Governance: Implement automated validation checks to ensure Audit-Ready data for global certifications like CBAM and ISO.
Scalability: Ensure the data architecture can scale to track Scope 3 emissions for hundreds of thousands of suppliers.
Required Qualifications
Education: from IIT or NIT (2024-2025 batch preferred).
Experience: 0 - 4 years. For freshers mandatory internship experience in Data Engineering or Big Data.
Technical Stack: * Languages: Python or Java (Mandatory).
Databases: Expert-level SQL PostgreSQL and NoSQL (MongoDB/Cassandra).
Tools: Familiarity with Spark Airflow Kafka or DBT.
Cloud: Hands-on experience with AWS or Azure Data Factory.
Soft Skills: A data-first mindset with extreme attention to detail.
Compensation & Growth
0-1 Year (2024-25 Batch Freshers): Up to (15 LPA) (including 10% Variable).
2-4 Years Experience: Up to (40 LPA) Total Cash Compensation.
The Opportunity: You will build the foundational data layer for a company that is defining a new category in Climate-Tech.
Why this role is High Demand
The Data Bottleneck: Most AI projects fail not because of bad models but because of bad data. Companies are paying a premium for engineers who can fix the data first.
Industrial Complexity: Processing data from a steel plant is significantly harder than processing web data. This makes Industrial Data Engineers a very rare and highly-paid breed.
Compliance Ready: With regulations like CBAM coming in data traceability (linking a product to its carbon source) is a legal requirement making this role a must-hire.
Summary of your 4 target High-Demand Roles:
Machine Learning Engineer (The Brains)
Full Stack AI Engineer (The Product)
Solution Architect (The Strategy)
Data Engineer (The Infrastructure)
Required Skills:
azuresqletldatasnowflakeairflowazure data factorykafkaawsspark
Key Skills
- Lean Manufacturing
- Six Sigma
- Continuous Improvement
- GM Vehicles
- Lean
- Industrial Engineering
- Value Stream Mapping
- Assembly Experience
- Warehouse Management System
- Autocad
- Kaizen
- Manufacturing
