Data Platform Engineer

Overview

Hybrid
Depends on Experience
Full Time
10% Travel

Skills

2+ years at a Seed to Series B startup
fast-paced startup
backend engineering
data infrastructure
ETL/ELT
Pandas
NumPy
Snowflake
Python
Linux
Flask/Django
SQL querying
modeling
optimization
DBT
Modern BI Tools
Git version controls

Job Details

Data Platform Engineer to architect and scale the systems behind our global sequencing logistics, lab workflows, and customer insights. This high-impact role combines backend engineering, data infrastructure, and analytics to drive operational excellence. You ll be responsible for managing terabytes of mission-critical data spanning scientific operations, shipment tracking, and product interaction, ensuring it is accessible, reliable, and actionable.

Key Responsibilities

  • Design, build, and maintain data pipelines that consolidate lab performance, logistics data, and user behavior.

  • Develop backend systems to support real-time delivery orchestration across 10+ labs worldwide.

  • Manage and optimize our data warehouse ecosystem (e.g., Snowflake, DBT) for performance and scalability.

  • Build models and tools to monitor system throughput, quality metrics, and operational bottlenecks.

  • Transform complex data into clear insights to inform product and business decisions.

  • Collaborate cross-functionally with engineers, scientists, and business stakeholders to align technical solutions with real-world needs.

  • Investigate anomalies in data flows and dig into root causes, upstream sources, and system behavior to resolve issues.

Minimum Qualifications

  • 5 10 years of experience in software or data engineering roles.

  • Minimum of 2 years at an early-stage startup (Seed to Series B, <100 employees).

  • BS, MS, or PhD in Computer Science or a related field from a top 40 U.S. university.

  • Deep SQL expertise (data modeling, optimization, and querying).

  • Strong Python skills, including experience with data libraries like Pandas and NumPy.

  • Proficiency with modern data stack tools (DBT, Snowflake) and Python web frameworks (Flask, Django).

  • Comfortable working with Git and Linux-based environments.

  • A strong sense of ownership and willingness to commit to a demanding, high-responsibility environment (60+ hours/week).

Preferred Qualifications

  • Background in biotechnology, genomics, or laboratory automation.

  • Experience building data platforms in logistics, scientific sequencing, or operational analytics.

  • Prior experience as a founder or early engineer at a data-intensive startup.

  • Familiarity with next-gen BI tools like Sigma.

  • Demonstrated success with personal or side projects that had real-world users or traction.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

About SmartTech Staffing Partners