Full-Time

Director of Data Engineering

Posted on 9/23/2025

Human Agency

Human Agency

11-50 employees

Full-service creative agency delivering AI-driven services

No salary listed

Remote in USA

Remote

Remote-friendly; occasional travel 10–30% for client activities; preference for candidates in St. Louis, MO and major tech hubs.

Category
Data & Analytics (3)
, ,
Required Skills
Power BI
Airflow
Data Science
SQL
Tableau
Looker
Snowflake
Requirements
  • 7+ years in data engineering/analytics engineering with ownership of production pipelines and BI at scale.
  • Demonstrated success owning and stabilizing production data platforms and critical pipelines.
  • Strong grasp of modern data platforms (e.g., Snowflake), orchestration (Airflow), and transformation frameworks (dbt or equivalent).
  • Competence with data integration (ELT/ETL), APIs, cloud storage, and SQL performance tuning.
  • Practical data reliability experience: observability, lineage, testing, and change management.
  • Operates effectively in ambiguous, partially documented environments; creates order quickly through documentation and standards.
  • Prior ownership of core operations and reliability for business-critical pipelines with defined SLOs and incident response.
  • Demonstrated client-facing experience (consulting/agency or internal platform teams with cross-functional stakeholders) and outstanding written/verbal communication (executive briefings, workshops, decision memos).
Responsibilities
  • Coordinate across data engineering, analytics, and data science leads; run operating cadences, triage priorities, and manage releases.
  • Map ownership and dependencies; reduce single points of failure; maintain a living service catalog and decision log.
  • Lead transition planning and knowledge transfer with internal teams and vendors while sustaining delivery.
  • Build, operate, and improve ELT/ETL pipelines across batch and streaming sources.
  • Manage orchestration (e.g., Airflow), transformations, environments, and CI/CD for analytics code.
  • Optimize warehouse performance (e.g., Snowflake) and cost.
  • Rapid discovery of existing pipelines and data contracts; map dependencies, SLAs/SLOs, and single points of failure; propose immediate stabilizations.
  • Implement monitoring/alerting, data quality checks, and tests with clear SLOs.
  • Maintain lineage/metadata visibility and role-based access controls.
  • Participate in an incident response rotation; maintain runbooks and postmortems.
  • Establish change-management controls (versioning, approvals, environment promotion) for analytics code.
  • Partner with analysts and business stakeholders to deliver trusted datasets and semantic models.
  • Support BI tools (Looker/Power BI/Tableau) and establish versioned, documented sources of truth.
  • Translate business needs into technical data solutions and clear option sets (impact, risk, effort).
  • Facilitate discovery/working sessions; align requirements and prioritize tradeoffs.
  • Prepare executive-ready updates: concise narratives, metrics, and decision logs.
  • Manage scope and expectations; escalate risks early; build trust and influence across engineering, analytics, and business teams.
  • Produce concise technical docs, decision logs, and release notes.
  • Translate technical tradeoffs into clear options for non-technical stakeholders.
  • Own day‑to‑day reliability for priority pipelines and critical dashboards; implement pragmatic monitoring/alerting.
  • Triage/resolve incidents; create or harden runbooks, playbooks, and on‑call rotations.
  • Establish lightweight governance: data quality checks, lineage visibility, access reviews, and change‑management basics.
  • Be able to read, debug, and improve existing pipelines; create new connectors/transformations as needed.
  • Standardize patterns (e.g., ELT with versioned transformations, environment promotion, CI/CD for analytics code).
  • Recommend and implement pragmatic tooling upgrades without destabilizing production.
  • Maintain a living service catalog and decision log.
  • Lead structured knowledge transfer sessions and create handover materials.
Desired Qualifications
  • Deep interest in Generative AI and Machine Learning.
  • Basic scripting ability in Python.
  • Practical Generative AI experience: shipped at least one end-to-end workflow (e.g., RAG) including ingestion, embeddings, retrieval, generation, and evaluation.
  • Working knowledge of LLM behavior (tokens, context windows, temperature/top-p, few-shot/tool use) and how to tune for quality/cost/latency.
  • Comfort with vector search (e.g., pgvector or a hosted vector store) and hybrid retrieval patterns.
  • Evaluation & safety basics: offline evaluation harnesses, lightweight online A/B tests, and guardrails for PII and prompt-injection.
  • MLOps for LLMs: experiment tracking, versioning of prompts/configs, CI/CD for data & retrieval graphs, and production monitoring (latency, cost, drift).
  • Python scripting for data/LLM utilities and service integration (APIs, batching, retries).
  • Familiarity with BI tools (Power BI/Tableau) and semantic layer design.
  • Exposure to streaming, reverse ETL, and basic MDM/reference data management.
  • Security & governance awareness (role‑based access, least privilege, data retention).

Human Agency is a full-service creative agency that combines marketing, technology, and business operations to help a range of clients—from startups to large corporations—achieve their goals. The company uses AI to boost human potential, enhancing marketing, product development, and operational effectiveness. It works by offering customized services such as web and mobile development, marketing campaigns, and business consulting, and also participates in venture investments by funding and supporting founders who are changing the world. Unlike firms that focus on a single discipline, Human Agency provides a holistic suite of services and revenue streams: service fees for projects and ongoing engagements, plus returns from its investments in startups. The company’s goal is to help clients grow and compete more effectively by integrating AI-enabled solutions with practical business strategies, while also backing entrepreneurs who aim to create meaningful impact.

Company Size

11-50

Company Stage

N/A

Total Funding

N/A

Headquarters

St. Louis, Missouri

Founded

2018

Simplify Jobs

Simplify's Take

What believers are saying

  • AI-driven services command premium pricing as enterprises prioritize efficiency and competitive advantage.
  • Portfolio companies become captive clients, creating recurring revenue and cross-selling opportunities.
  • Venture arm generates outsized returns if portfolio companies exit successfully, offsetting service revenue volatility.

What critics are saying

  • Name confusion with 4,411+ nonprofits named Human Service Agency blocks organic search visibility.
  • WPP's Hogarth AI platform delivers campaigns 30% cheaper, commoditizing boutique AI creative services.
  • 65% of AI startups fail post-2024; portfolio losses erode credibility and investment returns.

What makes Human Agency unique

  • Combines creative services with venture capital, funding founders while serving as their marketing partner.
  • Leverages AI across full service stack: development, strategy, operations, and investment decision-making.
  • Holistic approach tailors marketing, technology, and business operations to client needs simultaneously.

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Benefits

Remote Work Options

Performance Bonus

INACTIVE