Data Engineer - Salesforce

Amazon • Advertising • Cloud Platforms (IaaS & PaaS) • Python • Java • SQL • Apex • Tableau • Power BI • ETL/ELT • 2 months ago
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Salary
≈ $20k – $46k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Senior · 5+ years exp

First seen by Alion on Aug 21, 2026. Amazon scores A on the Alion truth index.

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Amazon

Amazon is an American technology and retail conglomerate founded by Jeff Bezos in 1994 as an online bookstore and headquartered in Seattle, Washington. It operates the world's largest online marketplace together with a global logistics network, physical grocery stores and a third-party seller platform that accounts for most units sold. Amazon Web Services, launched in 2006, is the leading public cloud provider and generates the majority of the group's operating profit, while advertising, Prime Video, Alexa devices and Kuiper satellite broadband round out the business.
amazon.com • HQ: Seattle, United States • Robotics AI • Logistics & Warehouse Robotics • Advertising • Logistics • Streaming & OTT Platforms • Cloud Platforms (IaaS & PaaS) • Marketplaces • 5000+ employees • Est. 1994
Tech stack of Amazon
Backed by General Catalyst, Kleiner Perkins, Plug and Play

We're looking for a Salesforce Data Engineer to build scalable data pipelines and enable seamless data movement between Salesforce and enterprise data platforms. In this role, you'll work on cloud-native data solutions, optimise ETL/ELT workflows, and support analytics by delivering reliable, high-quality data.

Responsibilities:

  • Design and develop data pipelines integrating Salesforce with enterprise systems and cloud data platforms.
  • Build and optimise ETL/ELT workflows for large-scale data processing.
  • Develop data models to support reporting, analytics, and business intelligence.
  • Integrate Salesforce using APIs and modern integration frameworks.
  • Ensure data quality, governance, security, and performance across data pipelines.
  • Collaborate with cross-functional teams to deliver scalable and reliable data solutions.

Requirements:

  • 5-10 years of experience in Data Engineering.
  • Strong experience with Salesforce data (Sales Cloud and/or Service Cloud).
  • Expertise in SQL and programming with Python or Java.
  • Hands-on experience with Salesforce APIs, ETL/ELT tools, and cloud platforms (AWS, Azure, or GCP).
  • Experience with modern data warehouses such as Snowflake, Databricks, Redshift, BigQuery, or Synapse.
  • Familiarity with orchestration tools like Airflow or Azure Data Factory.
  • Exposure to CI/CD, Git, and data modelling concepts.

Good to Have

  • Salesforce Data Cloud or Marketing Cloud experience.
  • Kafka, dbt, Tableau, or Power BI exposure.
  • Salesforce or Cloud certifications.
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