Data Analytics Engineer

Devsavant; United States; Remote; USD 140,000 - 180,000; Full time

Job summary

Devsavant is seeking a senior data-focused individual contributor for a remote-first analytics environment where data is the product. You will own reliability, release, and customer-facing correctness of core data products handling billions of rows and frequent updates.

You will monitor data quality, distinguish signal from issues, run root-cause investigations, and own end-to-end releases. Collaborate with Eng and Data Science; guide cross-functional squads and align with clients.

Qualifications

• 6+ years in data-focused roles.
• Expert-level SQL for large datasets.
• Experience with real-scale multi-table environments.
• Designing data quality test plans for aggregates.
• Collaborating with Eng and Data Science teams.
• Cross-functional project accountability and client communication.

Responsibilities

• Monitor data quality at pipeline stages and create scalable test plans.
• Distinguish real signal from data-quality issues using hypothesis testing.
• Lead root-cause investigations aimed at prevention.
• Own end-to-end data product release cycle for accuracy and reliability.
• Coordinate cross-functional squads and communicate plans to clients.
• Drive coverage expansion initiatives with commercial teams.
• Leverage AI to streamline workflows without adding QA overhead.

Skills

SQL

Data quality

Data pipelines

Testing and QA

Stakeholder mgmt

Job description

Role overview

A senior individual contributor position sits within a remote-first analytics organization where the data itself is the product. The work centers on owning the reliability, release, and customer-facing correctness of core data products that external clients consume. The role navigates genuinely messy data at scale, including billions of rows, weekly panel refreshes, and daily configuration shifts, where defensible judgment calls are routine.

Responsibilities

• Monitor data quality at each stage of the pipeline and build scalable aggregate-level test plans that validate outputs


• Distinguish real signal from data-quality issues using hypothesis testing to rule out sources of discrepancy


• Run root-cause investigations that end in prevention rather than one-off fixes


• Own the end-to-end data product release cycle, ensuring accuracy, reliability, and on-time delivery


• Project-manage cross-functional squads across multiple concurrent deadlines and communicate action plans directly to clients


• Take DRI ownership of coverage expansion initiatives from scoping through delivery, partnering with commercial teams


• Use AI to streamline workflows without adding QA overhead

Requirements

• 6+ years of experience in data-focused roles


• Expert-level SQL with a track record of mining large datasets for inconsistencies


• Experience at real scale with complex multi-table environments and frequent update cycles, not static extracts


• Experience designing data quality test plans that hold up in aggregate


• Comfort making defensible judgment calls when outcomes are genuinely unclear


• Direct collaboration experience with Engineering and Data Science teams


• Cross-functional project management accountability for business outcomes


• Customer-facing experience translating client feedback into technical feasibility

Nice to have

• Managing data vendors through selection, negotiation, and issue resolution


• Mentoring teammates on data operations best practices


• Background in data-as-a-product, market intelligence, or syndicated data


• Prior experience in a small, remote-first team

Benefits and work setup

LATAM-based, full-time role operating on US business hours. Remote-first environment, reporting to the VP of Data Operations.