Data Engineer (Industrial ETL & Infrastructure)- Bangalore

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Experience:

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The Business Context

#1 Carbon Accounting Platform for Industrial Manufacturing

ex-McKinsey Partners

The Role

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: B.Tech/M.Tech 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 ₹15,00,000 (15 LPA) (including 10% Variable).
• 2-4 Years Experience: Up to ₹40,00,000 (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)