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Salary
≈ $17k – $39k per year (Estimated)
Location
In office (Bengaluru, Gurgaon)
Experience
6+ years exp

First seen by Alion on Oct 26, 2026.

Overview
Company
Impact
Profile match
Whilter.AI is marketing that compounds: one connected engine that acquires, converts, and retains customers at scale, so every campaign makes the next one smarter.

Data Engineer (Priority Hires)

We are seeking two critical, seasoned Data Engineers focused on real problem-solving velocity rather than arbitrary years of tenure. This priority hiring track targets engineers capable of managing complex data emission patterns from SAP environments into Azure Databricks, designing resilient domain models across Finance, Procurement, and Sales, and engineering automated pipelines up to the Silver clean room layer.

Key Responsibilities:

- Architect and deploy high-velocity data extraction and emission frameworks fetching complex structures directly from SAP source systems into cloud landing nodes.

- Design and enforce robust data modeling semantics across critical corporate domains: Finance (GL, Cost Centers), Procurement (Vendor tracks, PO lifecycles), and Sales (Order books, fulfillment metrics).

- Construct scalable ingest pipelines transitioning raw structural emissions into the Bronze storage plane, utilizing PySpark and optimized Python runtimes.

- Build clean, decoupled processing paths transitioning raw data into the Silver layer (Medallion Architecture), ensuring schema evolution, data sanitation, and strict quality gates.

- Design and maintain data lakehouse patterns utilizing Delta Lake formatting to support concurrent read/write locks, ACID compliance, and low-latency downstream analytics.

Technical Requirements:

- Exceptional problem-solving track record with a focus on writing high-performance, maintainable data engineering code.

- Advanced capabilities in Python scripting, SQL optimization, and large-scale data transformations using PySpark.

- Direct engineering experience handling data emission, replication, or extraction logic from enterprise SAP landscapes.

- Practical execution history implementing multi-layered Medallion Lakehouse architectures on the Azure Databricks platform.

- Deep understanding of database normalization, dimensional modeling, and performance tuning strategies for distributed storage paradigms.

Total Experience: 6 - 9 years

Skills

Data Engineering, Azure Databricks, PySpark, Python, SQL, Delta Lake, Data Modeling

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