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TALPRO INDIA PRIVATE LIMITED

Data Engineer – Ratings Engine & Billing Transformation

Posted 25 Days Ago
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In-Office
Bengaluru, Bengaluru Urban, Karnataka, IND
Senior level
In-Office
Bengaluru, Bengaluru Urban, Karnataka, IND
Senior level
Build scalable telemetry and usage-data pipelines using AWS Glue, PySpark, Python, SQL, and Snowflake. Transform raw data into rated, validated, invoice-ready outputs for SAP billing and usage-based billing systems. Implement rating logic, data quality checks, reconciliation, audit trails, exception handling, monitoring, and CI/CD deployments. Optimize data models and pipelines while supporting batch and event-driven ingestion and collaborating with engineering, finance, billing, and operations teams.
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Data Engineer – Ratings Engine & Billing Transformation
Role Details
  • Role: Data Engineer – Ratings Engine & Billing Transformation
  • Primary Skills: AWS Glue, Snowflake, Python, PySpark, SQL, CI/CD
  • Domain Exposure: Usage-Based Billing, Rating Engine, SAP Invoice Feeds, Financial Data Processing
  • Experience / Location : 5 to 9 yrs/ Bengaluru- Hybrid
  • Budget: 22 LPA
  • Contract Duration: 12 months
Role Overview

We are seeking an experienced Data Engineer to join a large-scale Billing Transformation programme. The engineer will be responsible for sourcing telemetry data, building scalable data pipelines, supporting rating logic, and preparing billing-ready outputs for SAP invoicing.

This role requires strong hands-on experience in AWS Glue, Snowflake, Python, PySpark, SQL, and CI/CD practices. The candidate will also be responsible for implementing data quality checks, reconciliation controls, audit trails, exception handling, and operational monitoring to ensure billing accuracy.

This is a critical engineering role supporting the transformation of raw telemetry usage data into rated, validated, and invoice-ready billing data.

Key Responsibilities
Data Ingestion & Pipeline Development
  • Build and maintain data ingestion pipelines from telemetry and usage data sources.
  • Develop scalable ETL/ELT pipelines using AWS Glue, PySpark, Python, and SQL.
  • Support both batch and event-driven data ingestion patterns.
  • Ensure data pipelines are reliable, performant, scalable, and cost-efficient.
Snowflake Data Engineering
  • Create and maintain curated usage datasets in Snowflake.
  • Design efficient data models, tables, views, and processing layers for downstream billing use cases.
  • Optimize SQL queries, warehouse usage, partitioning strategies, and performance.
  • Support analytics, validation, and reconciliation use cases on Snowflake.
Ratings Engine & Billing Transformation
  • Support implementation of rating logic for usage-based billing.
  • Prepare billing-ready datasets for invoice processing.
  • Generate data outputs and feeds required for SAP invoicing.
  • Work on pricing, usage calculation, billing rules, and financial data transformation logic.
  • Ensure raw telemetry data is transformed into accurate, validated, and invoice-ready records.
Data Quality, Reconciliation & Audit Controls
  • Design and implement data quality checks across ingestion, transformation, rating, and billing layers.
  • Build reconciliation controls to validate data completeness, accuracy, and consistency.
  • Implement audit trails for billing data movement and transformation.
  • Create exception-handling and error-management processes for failed or inconsistent records.
  • Support root cause analysis for billing discrepancies and data issues.
CI/CD, Monitoring & Operations
  • Build and support CI/CD pipelines for data engineering deployments.
  • Work with tools such as GitHub Actions, GitLab CI, Jenkins, AWS CodePipeline, or similar.
  • Implement operational monitoring, alerts, dashboards, and pipeline health checks.
  • Maintain technical documentation, runbooks, and support procedures.
  • Collaborate with engineering, finance, billing, and operations teams to ensure smooth delivery.
Required Skills & Experience
Technical Skills
  • Strong hands-on experience in data engineering, ETL/ELT development, and large-scale data pipeline design.
  • Experience with:
    • AWS Glue
    • PySpark
    • Python
    • SQL
    • Cloud-based data processing
  • Strong experience working with Snowflake as a data warehouse or enterprise data platform.
  • Advanced SQL skills for:
    • Data analysis
    • Validation
    • Troubleshooting
    • Query optimization
    • Performance tuning
  • Experience with batch and event-driven ingestion patterns.
  • Understanding of:
    • Data modelling
    • Partitioning
    • Performance tuning
    • Cost optimization
    • Scalable pipeline design
Billing & Financial Data Skills
  • Good understanding of one or more of the following:
    • Usage-based billing
    • Rating engines
    • Invoice feeds
    • SAP invoice integration
    • Financial data processing
    • Billing reconciliation
  • Experience transforming usage/telemetry data into billing-ready outputs will be strongly preferred.
Data Quality & Governance
  • Experience building:
    • Data quality checks
    • Reconciliation frameworks
    • Audit controls
    • Exception handling processes
    • Error logging and monitoring workflows
  • Ability to ensure data accuracy, traceability, and reliability across the billing lifecycle.
DevOps & Engineering Practices
  • Hands-on experience with CI/CD tools such as:
    • GitHub Actions
    • GitLab CI
    • Jenkins
    • AWS CodePipeline
    • Similar deployment tools
  • Familiarity with Git-based workflows and release management.
  • Ability to write clean, maintainable, and well-documented code.
  • Experience working in Agile delivery environments.
Preferred Skills
  • Experience working on large-scale Billing Transformation, Finance Transformation, or Order-to-Cash initiatives.
  • Exposure to SAP invoicing, SAP billing integration, or downstream finance systems.
  • Experience with operational dashboards and alerting tools.
  • Knowledge of data governance, lineage, and metadata management.
  • Experience handling high-volume telemetry or usage datasets.
Soft Skills
  • Strong analytical and problem-solving skills.
  • High attention to detail, especially around billing accuracy and reconciliation.
  • Good communication and stakeholder collaboration skills.
  • Ability to work with technical, finance, billing, and operations teams.
  • Ownership mindset with the ability to deliver in transformation-driven environments.


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