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Database Engineer
Database EngineerSNH Capital Partners • Austin, TX, US
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Database Engineer

Database Engineer

SNH Capital Partners • Austin, TX, US
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About Us

At SNH AI, we're building the future of work : AI-powered Autonomous Employees who perform entire job roles, not just tasks, to empower organizations to scale efficiently. We're based in the heart of Downtown Austin, TX with breath-taking views. We're an AI startup that thrives on curiosity, bold thinking, and a passion for solving hard problems. Our team is rapidly growing, and every line of code you write will have a direct impact on the products and customers we serve. We're shaping the future of how work will be done : humans working alongside Artificially Intelligent systems that infinitely scale their productivity and output.

Why You'll Love Working Here

  • A collaborative startup culture where your voice matters.
  • Work directly with modern LLMs and applied AI tooling.
  • Fast-moving, impact-driven environment with strong engineering peers

What We're Looking For

We are seeking a Database Engineer with strong data analysis skills and deep experience on Google Cloud Platform (GCP) to support personalized lead engagement based on real-time behaviors and CRM insights with some exposure to AI and machine learning.

In this role, you'll build data pipelines and prototypes that integrate CRM, credit, and behavioral data including response times, click-through behavior, and inbound call interactions to create dynamic segmentation and deliver conversion-optimized "buy now" messages. Your work will be foundational to how we engage leads, drive sales, and improve overall customer experience.

In-person work at the office to drive productivity and collaboration. (No remote, please) – we cover your parking Downtown.

Key Responsibilities

  • Design and implement scalable, cloud-based data pipelines and warehouses using GCP services : BigQuery, Cloud Composer (Airflow), Dataflow, Cloud Functions, and Pub / Sub.
  • Build ELT workflows to extract and unify data from CRMs (e.g., Salesforce, HubSpot), marketing platforms, credit data providers, and behavioral sources.
  • Capture and analyze lead behavior signals including :
  • Response times to outreach
  • Click-through rates on emails, ads, and in-app prompts
  • Inbound call activity and sales team interactions
  • Develop behavioral segmentation models to target leads based on urgency, interest, and likelihood to convert.
  • Prototype personalized engagement triggers and "buy now" messaging strategies based on combined behavior and credit profile data.
  • Partner with marketing and growth teams to deploy and optimize campaigns tailored to lead behavior and funnel stage.
  • Conduct exploratory data analysis (EDA) to uncover key trends and insights that drive personalized outreach.
  • Monitor and report on campaign and segment performance through Looker / Looker Studio dashboards.
  • Ensure data integrity, privacy, and regulatory compliance (e.g., GDPR, SOC2, FCRA).
  • Maintain flexibility to work across legacy and cloud systems, including SQL Server, Oracle, and PostgreSQL.

    • Required Qualifications

  • Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or a related field or equivalent experience.
  • 5+ years of experience in data engineering or database roles with a strong emphasis on data analysis, customer engagement & ad-hoc reporting.
  • 3+ years of hands-on experience with Google Cloud Platform, including BigQuery, Dataflow, Pub / Sub, and Cloud Composer. (AWS / Azure OK)
  • Proficiency in SQL (across multiple platforms) and Python for data processing and modeling. Ability to turn raw data into meaningful insights to understand patterns and trends.
  • Experience building and maintaining data pipelines that feed into marketing and sales engagement systems.
  • Demonstrated ability to capture and use behavioral data (e.g., clickstreams, email response rates, phone call metadata) to optimize lead handling and conversion strategies.
  • Familiarity with enterprise databases including SQL Server, Oracle, and PostgreSQL.
  • Hands-on experience with CRM systems (Salesforce, HubSpot) and marketing automation platforms (Marketo, Pardot, Mailchimp).

    • Preferred Qualifications

  • Experience with ETL tools (e.g., Azure Data Factory, Airbyte, Cloud Composer, Data Flow ) and / or Customer Data Platforms (CDPs).
  • Experience in designing, building and deploying AI and machine learning models in production environments. Simulation based learning of training and validation data.
  • Background in campaign optimization, A / B testing, and predictive lead scoring.
  • Versed in data governance, privacy, and security best practice.
  • Familiarity with call tracking systems, IVR analytics, or conversational AI platforms, Data Modeling is a plus.
  • Knowledge of data compliance standards and secure handling of personal and financial data.

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