Lead Data Engineer

Job Category

Software Engineering

Job Details

**About Salesforce**

Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.

Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place Agentforce is the future of AI, and you are the future of Salesforce.

**Lead Data Engineer**
**Mexico City | Mex**
**Hybrid**:
**Role Overview**
Lead the design and delivery of scalable data solutions that power business insights and innovation. Drive architecture, quality, and process excellence across batch and real-time data systems while mentoring a high-performing engineering team.

**What You'll Do**:
Lead end-to-end solution design for data products integrating batch and streaming pipelines.
Define and evolve solution architecture to deliver reliable, scalable, and consistent data insights.
Enhance data quality through proactive issue detection and source-level validation.
Optimize workflows and resources to maximize efficiency and performance.
Set engineering standards—advocate best practices, automation, and code quality.
Drive continuous improvement of shared data platform tools, processes, and methodologies.
Architect, build, and maintain automated, scalable pipelines using dbt, Snowflake, Informatica, and Airflow.
Unify and calibrate data from multiple sources to ensure accuracy and consistency.
Collaborate cross-functionally with data ingestion, platform, and product teams on instrumentation and data flow.
Develop and maintain robust datasets supporting modeling, analytics, and production use cases.
Integrate emerging technologies to strengthen data management and engineering capabilities.
Support data analysis and QA, ensuring ongoing integrity and reliability.
Mentor and guide engineers, fostering growth and technical excellence.

**Desired Skills & Experience**
Proven expertise in handling large data environments for over 8 years, utilizing modern data stack tools such as dbt, Snowflake, Informatica, and Apache Airflow.
Strong background in data modeling, ETL/ELT design, and building scalable, automated data pipelines.
Hands-on experience architecting and maintaining cloud-based data platforms with a focus on performance, reliability, and cost efficiency.
Deep understanding of data quality, governance, and observability to ensure trusted, consistent insights.
Skilled in SQL and Python, with experience in version control, CI/CD, and workflow automation.
Demonstrated ability to integrate batch and real-time data processes across diverse systems and sources.
Experience leading data engineering teams, setting technical direction, and fostering best practices in design, testing, and deployment.
Strong collaboration skills, with the ability to partner effectively across product, analytics, and platform teams.
Passion for continuous improvement, innovation, and enabling data-driven business outcomes.

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