Lead / Staff Backend Engineer (Data Platform)

Different • Marketing Automation • Marketing & Sales AI • Python • Java • SQL • 9 hours ago
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Salary
≈ $23k – $58k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Staff · 8+ years exp

First seen by Alion on Oct 23, 2026.

Overview
Company
Impact
Profile match

Different

Different is a B2B SaaS marketing platform that builds AI-driven tools around business goals to enable deeper customer engagement and transform how businesses plan and execute marketing.
different.ai • HQ: Bengaluru, India • Marketing & Sales AI • Marketing Automation • Est. 2023
Tech stack of Different

Responsibilities:

  • Design, develop, and deliver end-to-end services for Different.ai 's innovative platform.
  • Solve complex engineering challenges, including building high-throughput data pipelines for machine learning jobs handling petabyte-scale data.
  • Lead and mentor a team of dynamic engineers, fostering a collaborative and innovative environment.
  • Take ownership of critical architectural decisions.


Requirements:

  • Experience: 7-12 years in software and data engineering.
  • Solid understanding of data architecture principles and big data technologies/tools & Distributed data systems.
  • Experience with workflow orchestration tools like Apache Airflow, Dagster, Composer, and Airbyte, etc.
  • Experience with Real-time streaming (Kafka, Pulsar, Flink) & Query engines (Trino, Presto, Druid)
  • Experience with Data lakehouse architectures (Iceberg, Delta Lake, Hudi) & Batch processing (PySpark/Spark, Hadoop)
  • Advanced understanding of cloud platforms (AWS, GCP, Azure), modern data warehouses (Databricks, Snowflake, and Redshift), and databases (SQL family databases, MongoDB, and ElasticSearch).
  • Deep expertise in Java. Python and GoLang, etc.
  • Proficiency in Kubernetes, CI/CD tools, and deploying software solutions on-premises.

Skills

Golang, Big Data, Python, Java, Spark, Architecture, Airflow, Kafka, Pulsar, Flink, Presto, Druid, Delta Lake, Batch Processing, Distributed Systems

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