Director of Software Engineering, Data

Salesforce

Confirmed live today High trust
Remote

Quick summary

Work type
Remote
Location
San Francisco, CA
Salary
$197,300–$313,700 / yr
Employment
Full-time
Posted
2 days ago
Freshness
Confirmed live today

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $212k
This role $256k
$145k most similar roles pay here $332k

This role pays more than 73% of similar roles. Most pay $164,525–$259,000 — the shaded band above. At the midpoint, this role pays about $256k versus about $212k for comparable roles.

Based on 240 similar postings.

Employer

About Salesforce

Salesforce is the world''s leading customer relationship management (CRM) platform, offering cloud-based software for sales, service, marketing, analytics, and application development. Industry: Enterprise Software & Cloud Computing

Salesforce currently has 144 open roles on FindRole.

Listed pay typically runs $148,500–$227,000 across 110 roles with salary data.

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At a glance

TL;DR · Director of Software Engineering, Data

Director of Software Engineering (Data) leads the Data Engineering team to oversee technical strategy and execution for enterprise-scale data ingestion platforms. This role involves managing a team of senior engineers to build high-volume, high-throughput batch and real-time systems that power analytics, ML models, and AI agents. The candidate will architect scalable pipelines and ETL/ELT workflows while optimizing data models across Snowflake, Data360, and lakehouse environments. Key technologies include MuleSoft, Informatica, Spark, dbt, Iceberg, Kafka, and Airflow, alongside proficiency in SQL and Python. The role addresses the challenge of ingesting data from over 100 enterprise systems into a unified infrastructure that ensures reliability, security, and observability. By establishing standardized patterns and automated frameworks, the leader ensures the platform remains scalable and accessible for internal teams to support complex business operations.

What you'll do

  • Define and execute the technical strategy and roadmap for enterprise-scale data ingestion platforms.
  • Architect and operate high-volume, high-throughput batch and real-time data ingestion systems using Spark, Kafka, and Snowflake.
  • Design scalable data pipelines and ETL/ELT workflows while ensuring platform security, reliability, and performance.
  • Manage a team of senior data engineers through mentorship, coaching, and career development support.
  • Establish engineering best practices including architecture reviews, CI/CD, testing, and documentation.
  • Partner with cross-functional teams to translate complex business requirements into technical execution plans.
  • Drive platform scalability through automation, reusable frameworks, and self-service capabilities for internal teams.

What we're looking for

  • 15+ years of data engineering experience with a focus on data ingestion and cloud-based warehouse/lakehouse platforms.
  • 8+ years of engineering leadership and people management experience, ideally managing senior and staff-level engineers.
  • Proven experience architecting and operating high-volume, high-throughput enterprise data ingestion platforms.
  • Deep hands-on experience with Snowflake for architecture, performance optimization, security, governance, and cost management.
  • Strong expertise with Apache Spark for large-scale distributed processing and Apache Kafka for event-driven architectures.
  • Proficiency in SQL and at least one general-purpose programming language, preferably Python.
  • Experience designing lakehouse architectures using Apache Iceberg or comparable open table formats.
  • Experience with Salesforce data ecosystems (Data360) and developing AI agents or agentic workflows (preferred).

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