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Senior Analytics Engineer

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Location

Atlanta, GA; Plano, TX; Wichita, KS

Posted

Today

Koch Technologies HR Technology team is looking for a Sr. Analytics Engineer to help build the data foundation behind Koch Communications & Marketing's (KCM) measurement priority. In this role, you will build and maintain the data products that provide a trusted view of how communications and marketing efforts influence audience behavior, engagement, and business results. You will connect data across systems, develop scalable pipelines and analytics solutions, and deliver insights that improve decision-making, optimize investments, and increase measurement maturity across the business. You will also leverage AI to accelerate development and create intelligent analytics experiences, including natural-language access to data, anomaly detection, and automated insight generation.

Our team

People Data & Insights is a capability within the HR Technology organization of Koch Technology. We execute Koch's HR data management and analytics initiatives through holistic architecture, design, development, and support. We partner across Koch businesses and capabilities to ensure people data is reliable, defined, secure, accessible, and managed. Through data products, advisory services, governance, and analytics, we help make data a trusted asset that enables leaders to make informed, profitable decisions.

What you will do

  • Design, build, and maintain data pipelines, analytical models, dashboards, and AI-enabled data products that connect marketing, recruiting, and operational data into actionable insights.
  • Integrate and model data from multiple platforms, building scalable solutions that connect activities, outcomes, and business value across the customer and applicant journey.
  • Establish trusted data foundations through metric governance, data quality testing, monitoring, lineage, and documentation.
  • Apply AI and automation to accelerate development and enhance analytics experiences, including anomaly detection, natural language querying, insight generation, and entity resolution.
  • Partner closely with business stakeholders to translate requirements into scalable, production-ready solutions that improve decision making.
  • Rapidly learn new technologies, platforms, and business domains, leveraging strong data engineering fundamentals to solve complex problems.
  • Collaborate with technical and domain experts across the organization, engaging the right specialists while maintaining ownership for delivering business outcomes.
  • Support adoption through user enablement, documentation, continuous improvement, and validation that solutions drive measurable action and results.
  • Challenge existing approaches when appropriate, using curiosity, customer focus, and business context to identify better ways to create value.

Who you are (basic qualifications)

  • Experience building and operating production data pipelines and dimensional or analytical data models, including ELT/ETL, orchestration, and a transformation framework such as dbt or an equivalent.
  • Strong SQL and working proficiency in Python for data engineering and analysis.
  • Experience integrating data from multiple SaaS and web platforms through APIs, including incremental loads, schema drift, and rate limits.
  • Experience delivering analytics and dashboard solutions in a modern BI platform, including semantic or metric layer design.
  • Demonstrated hands-on use of AI and LLM tooling to accelerate engineering work, to deliver AI-enabled data products, or both.
  • Experience with data quality practices, including testing, monitoring, lineage, and documentation.
  • Experience working directly with business partners, or alongside a business-facing advisor, to translate requirements into delivered solutions.

What will put you ahead

  • Hands-on experience with web, marketing, and work-management platforms such as GA4, Google Search Console, Google Tag Manager, Kentico, Avature, FirstUp or TailoredMail, Sprout Social, and Workfront.
  • Experience with digital measurement concepts, including event and tagging design, audience and engagement analytics, content and journey effectiveness, attribution, and conversion or funnel analysis.
  • Experience building agentic or RAG-based applications, evaluation harnesses, or AI-assisted analytics experiences that reached real users.
  • Forward deployed, embedded, or solutions engineering experience: rapid prototyping with a partner team followed by productionization.
  • Experience with people analytics, workforce analytics, and HR data.
  • Experience with cloud data platforms such as Azure, Databricks, Snowflake, or Microsoft Fabric, and with modern data governance practices.
  • Experience with marginal analysis, experimentation, or A/B testing frameworks that support continue, start, and stop decisions.

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