Multitude Insights

Technology

PrincipalDataEngineer

₹60–90L ~AI est. Remote FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Principal Data Engineer at Multitude Insights. Skills: Data infrastructure, Data platform, Data engineering. Architect core data infrastructure. Maintain core data infrastructure”

Industry & Context.

Technology

What They're Looking For.

Must Have

10+ years of data engineering experience, Significant time in senior, staff, or principal-level roles, Deep expertise in data pipeline design, Deep expertise in distributed data systems, Track record of owning complex production data infrastructure, Proven experience with data modeling at scale, Proven experience with data ingestion at scale, Proven experience with data transformation at scale, Proven experience with data orchestration at scale, Proficiency in SQL, Experience with modern data warehousing technologies, Experience establishing data quality frameworks, Experience establishing data observability frameworks, Experience setting technical direction at an organizational level, Communication skills, Ability to make complex data architecture decisions legible to non-technical stakeholders

Nice to Have

Prior startup experience strongly preferred, Mission-critical environment experience strongly preferred, Hands-on experience with CI/CD pipelines, Hands-on experience with cloud data infrastructure, Experience with AWS at scale, Experience with Databricks at scale

What You'll Do.

Architect core data infrastructure

Maintain core data infrastructure

Design data pipelines

Design data warehousing

Build data warehousing

Design data ingestion

Design data transformation

Build data transformation

Design orchestration systems

Build orchestration systems

Own data platform scalability

Own data platform reliability

Own data platform security

Ensure high-quality data accessibility

Establish data engineering best practices

Establish data modeling best practices

Establish pipeline design best practices

Establish observability patterns best practices

Drive data quality initiatives

Drive observability initiatives

Partner with engineering teams

Partner with product teams

Partner with analytics teams

Understand data needs

Translate data needs into technical solutions

Mentor engineers on data engineering principles

Mentor engineers on data engineering patterns

Contribute to team development

How You'll Work.

Team & Collaboration

Engineering teams; Product teams; Analytics teams

Communication Scope

Make complex data architecture decisions legible

Full Job Description

ABOUT MULTITUDE INSIGHTS Multitude Insights builds modern tools for public safety agencies. Our flagship product, BLTN, is a real-time, AI-powered bulletin sharing platform that replaces the legacy email workflows police departments have relied on for decades. By enabling officers and analysts to easily create, search, and link bulletins across agencies, we’re turning static documents into actionable intelligence, faster, safer, and more connected. We’re a venture-backed team of engineers, public safety professionals, and veterans working closely with law enforcement customers across the country. Our mission is to give the people who keep us safe the tools they actually need. THE ROLE We’re looking for a Principal Data Engineer to design, build, and maintain the core data infrastructure that powers BLTN and the broader Multitude platform. This isn’t just a pipeline job, you’ll be the primary technical authority on all things data, shaping the architecture that enables reliable, high-quality data access across the organization. You’ll work closely with the VP of Engineering, product, and analytics stakeholders to translate real-world data needs into robust, scalable solutions, while setting the standards and patterns that the rest of the engineering team builds on. RESPONSIBILITIES • Design & Build: Architect and maintain the company’s core data infrastructure, including pipelines, warehousing, ingestion, transformation, and orchestration systems. • Own the Data Platform: Take end-to-end responsibility for the scalability, reliability, and security of the data platform ensuring high-quality data is accessible across the organization. • Set the Standard: Establish and own data engineering best practices, including data modeling, pipeline design, and observability patterns that the broader team can build on. • Champion Data Quality: Drive data quality and observability initiatives across the platform, ensuring stakeholders can trust the data they rely on. • Collaborate

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