Data Operations Engineer - Minneapolis, MN

Datasite; Minneapolis (MN); Hybrid; USD 99,000 - 172,700; Full time

Benefits offered by this job

Health insurance

Retirement savings plan

Paid time off

Diverse and inclusive workplace

Job summary

Datasite in Minneapolis is looking for a Data Operations Engineer who will own the lifecycle of partner data across systems. Responsibilities include designing and maintaining data pipelines, implementing monitoring, and mentoring team members.

The ideal candidate has strong SQL skills, experience with Snowflake and Airflow, and excels in engineering and collaboration. The role offers a hybrid work model and competitive compensation within a salary range of $99,000 to $172,700.

Qualifications

• Strong experience designing and operating data pipelines with defined SLAs.
• Expert SQL skills to handle large datasets.
• Hands-on experience with major data tools like Snowflake, dbt, and Airflow.

Responsibilities

• Design and maintain ingestion pipelines and data products.
• Implement monitoring and self-healing mechanisms.
• Mentor engineers and foster modern data practices.

Skills

SQL

Snowflake

dbt

Airflow

Data pipeline management

Job description

Job Overview

As a Data Operations Engineer at Datasite you own the full lifecycle of partner data as it moves through our systems—ingestion, transformation, validation and reconciliation—bringing the monitoring and SLA discipline that sophisticated partners expect. You balance partner trust, engineering velocity and long‑term data platform health while enabling intelligent, contract‑driven data exchange across our partner ecosystem.

Responsibilities

• Design, build and maintain ingestion pipelines, transformation layers, reconciliation processes and partner‑facing data products using Snowflake, dbt, Airflow and schema registries.
• Implement monitoring, alerting, runbooks and self‑healing mechanisms to identify and remediate issues before they become partner‑visible.
• Translate pipeline design trade‑offs and SLA commitments for diverse stakeholders.
• Evaluate trade‑offs across freshness, accuracy, latency and cost, and simplify pipelines to reduce data debt.
• Own ambiguous data challenges—mismatched schemas, silent failures, partial loads, reconciliation gaps—applying strong diagnostics to root causes and deliver resilient, auditable solutions.
• Mentor engineers and analytics contributors, fostering continuous learning and hands‑on adoption of modern and AI‑augmented data practices.
• Collaborate with Product, Engineering and partner teams to drive cross‑platform improvements and influence data architecture decisions that incorporate AI‑augmented capabilities.
• Support hiring by setting technical and cultural expectations and ensuring alignment with Datasite’s values.

Qualifications

• Strong experience designing and operating data pipelines with defined latency, freshness and accuracy SLAs.
• Expert SQL skills and proven ability to work with large, complex datasets across diverse partner schemas.
• Hands‑on experience with Snowflake, dbt, Airflow and schema registries.
• Practical, in‑the‑workflow use of agentic tooling to accelerate schema mapping, anomaly detection, data profiling and pipeline debugging.
• Track record of building monitoring, alerting, runbooks and reconciliation processes for systems with external commitments.
• Ability to ramp quickly on new partner ecosystems, data formats and domains.
• Excellent collaboration, communication and cross‑team influence skills.
• Experience leading work in ambiguous, fast‑moving environments.

Benefits

We offer competitive compensation, a hybrid work model with a minimum of two on‑site days per week, and a full suite of benefits including health (medical, dental, vision) insurance, a retirement savings plan, paid time off and other employee benefits.

Base salary range: $99,000.00 – $172,700.00
Datasite reserves the right to modify this pay range at any time.

Our company is committed to fostering a diverse and inclusive workforce. We are an equal opportunity employer and make all employment decisions without regard to race, color, religion, sex, gender identity, sexual orientation, age, national origin, disability, protected veteran status or any other protected characteristic.