Anadea

We are looking for a highly autonomous Senior Product Designer (UX/UI) to join our team for a high-intensity, short-term engagement. If you are a strategic thinker who can bypass the traditional onboarding ramp-up and immediately drive design value across multiple streams, we want to hear from you.
 

🗓 Contract Overview

• Duration: 3 Months (July, August, September)
• Location: Remote
• Seniority: Senior level
   

🎯 Key Responsibilities

• Multi-Project Management: Deliver end-to-end design support for 3–4 projects simultaneously.
• Instant Integration: Hit the ground running on day one with zero ramp-up time required.
• Business-Driven Design: Create impactful UX/UI solutions that balance user needs with business goals.
• Rapid Experimentation: Leverage AI tools to streamline user research and accelerate design prototyping.
• Mobile Excellence: Design seamless, intuitive experiences tailored specifically for mobile platforms.
   

💻 Required Profile

• Autonomy: Proven track record of working independently with minimal supervision.
• Mindset: Strong product orientation and a deep understanding of business metrics.
• Tooling: Advanced proficiency in Figma and seamless workflow management within Jira.
• Innovation: Active experience using AI tools for research, brainstorming, and quick testing.
• Languages: Fluent English (written and spoken). Conversational or professional Spanish is a strong plus.

The Mission
Are you a cloud architect who finds beauty in a perfectly orchestrated pipeline? Do you believe that “manual” is a four-letter word? We are looking for a Senior SRE specialized in BI
Ecosystems to join our mission-critical Infrastructure team.
In this role, you won’t just “maintain” systems; you will be the master weaver connecting our advanced Data Analytics tools with a rock-solid, automated GCP/AWS backbone. You will bridge the gap between traditional Business Intelligence and modern Cloud Engineering, ensuring our data flows are fast, our visualizations are seamless, and our infrastructure is invisible.

What You Will Do
1. Master the Orchestration (GCP & GKE)
You will take full ownership of our Google Kubernetes Engine (GKE) clusters. This isn’t just about pods and services; you’ll manage advanced networking (VPC Service Controls, Shared VPC) and high-availability node configurations to ensure our data platforms never skip a beat.
2. Advance Data Architectures (Lakehouse)
You will design and support a unified Data Lakehouse architecture by integrating BigQuery and Cloud Storage. Your mission is to break down silos, ensuring that our raw data and analytical models coexist in a single, high-performance ecosystem. You will implement robust governance and security policies that ensure data quality and accessibility, providing a “single source of truth” that is both scalable and cost-effective
3. Evangelize Infrastructure as Code (IaC)
Our goal is 100% immutability. You will use Terraform to automate the entire lifecycle of our GCP resources—from Compute Engine and Cloud Run to Cloud SQL—ensuring consistency across Dev, Staging, and Production.
4. Empower DataViz Excellence
You will be the enabler for our Data Analysts. You’ll deploy, optimize, and scale Qlik Sense, Tableau, or Similars environments on GCP, handling everything from SSO/IAM authentication to high-performance connectivity with our backend data sources.
5. Hybrid Cloud & Legacy Modernization
Complexity is our playground. You will manage critical AWS resources (EC2, S3) and ensure seamless interoperability with GCP. Simultaneously, you will lead the charge in migrating legacy monolithic systems into modern, microservices-based architectures.
6. Data Engineering Collaboration
Working side-by-side with Data Engineers, you’ll help build and maintain robust pipelines using Cloud Dataflow, Cloud Composer (Airflow), and BigQuery. You ensure that the “plumbing”
of our data world is leak-proof and high-performing.
7. Reliability, Security & FinOps
● CI/CD: Design sophisticated pipelines (GitLab CI/GitHub Actions) integrating DevSecOps best practices.
● Observability: Implement deep monitoring using Google Cloud Operations Suite and Grafana.
● FinOps: Be the guardian of our budget, identifying and eliminating cloud waste through smart optimization.

Who You Are (Requirements)
● Cloud Expert: Proven experience managing complex environments in Google Cloud Platform (GCP) and AWS.
● Data Architect: Deep understanding of Data Lakehouse models and governance.
● Kubernetes Pro: Deep knowledge of GKE, including advanced networking and security policies.
● Terraform Ninja: Ability to write modular, scalable, and secure IaC.
● BI Infrastructure Savvy: Experience deploying and tuning enterprise visualization tools (Tableau, Qlik, or Power BI).
● Automation Mindset: Strong scripting skills (Python, Bash, or Go) and mastery of CI/CD engines.
● Data-Driven: Familiarity with Big Data tools like Airflow, BigQuery, and Dataflow.
● Security-First: Solid understanding of encryption, IAM roles, and network security standards.

Why Join Us?
● Impact: You are not a cog in the machine; you are building the machine.
● Tech Stack: Work with the latest tools in the Cloud and Data world (Lakehouse, GKE).
● Culture: We value technical excellence, proactive problem-solving, and a “fail fast, learn faster” mentality.
● Growth: We invest in your certifications and continuous learning.
Ready to redefine how BI meets SRE? If you are a builder who loves solving the puzzle of high-scale data infrastructure, we want to meet you.

Apply now and let’s build the future of data infrastructure together!

Role Type: Contract / Fixed-Scope Consulting Engagement
Duration: 2–3 months (10–12 weeks)
Allocation: Full-time or near full-time (4–5 days/week preferred)
Location: Remote (Must overlap with Spain / CET ± 6 hours)
Languages Required: Spanish (C1+) and English (B2+)
 

The Opportunity

We are looking for a hands-on Senior Data Science / Analytics Engineering Consultant to audit, redesign, and rebuild our core chargeback estimation and revenue estimation models.

This is a critical, end-to-end project. You will turn existing prototypes into production-grade pipelines within our modern data stack (dbt on Databricks & Python). Additionally, you will design and build a lightweight, business-facing scenario tool that enables finance and operations stakeholders to run “what-if” revenue simulations.

Our Technical Philosophy: Parsimony Over Black Boxes

We explicitly favor simple, highly interpretable, parametric approaches. If your first instinct for a forecasting problem is to throw an XGBoost ensemble, a deep learning model, or an LLM at it, this is not the project for you.

We build models where every parameter carries an explicit business meaning that can be explained to non-technical stakeholders in plain language (e.g., “If price increases by 10%, conversion drops by X% because our calculated price elasticity is −1.3”).
 

Scope of Work & Deliverables

• Phase 1: Discovery & Audit (Weeks 1–2): Review current estimation models (assumptions, dbt lineage, validation methods). Reconcile historical model outputs against actual accounting figures for the last 12–24 months to quantify bias and error. Deliver a written findings report.
• Phase 2: Redesign (Weeks 3–4): Propose the target parametric methodology for each model (granularity, refresh cadence, uncertainty quantification) and secure stakeholder sign-off.
• Phase 3: Rebuild (Weeks 5–9): Productionize the new models in dbt, Databricks, and Python. Use curve-based formulations with fitted historical parameters and clear confidence intervals. Implement strict unit/dbt testing and MLflow tracking.
• Phase 4: Scenario Tool (Weeks 9–10): Build a lightweight business interface (e.g., Streamlit on Databricks or a parameterized Databricks SQL dashboard). Users must be able to input hypotheses (price ±X%, volume ±Y%, mix shifts) and instantly view projected net impact with uncertainty bands.
• Phase 5: Handover (Weeks 11–12): Conduct knowledge transfer sessions, deliver runbooks/model cards, and provide a 2-week post-handover bug-fix support window.
   

Your Profile

• Experience: 5–8+ years in Data Science, Quant Analytics, or Senior Analytics Engineering.
• Production Ownership: Proven track record of owning financial-estimation or forecasting models in production end-to-end.
• The “Parsimony” Mindset: Demonstrable expertise in parametric/curve-based modeling (price elasticity, cohort survival curves, demand curves, GLMs) over black-box ML.
• Stakeholder Tooling: Experience building clean “what-if” tools or financial planning interfaces for business leadership.
• The Stack: Advanced Python (pandas, numpy, scikit-learn, statsmodels, and/or scipy.optimize), production dbt (incremental models, snapshots, tests), and Databricks (PySpark, Delta, workflows).
• Domain Knowledge: Direct experience in payment risk, chargebacks, refund/dispute modeling, revenue forecasting, cohort LTV, or pricing analytics.
• Communication: Exceptional ability to cross-reference data science outputs with strict financial accounting figures.
• Languages: Spanish (C1+) is mandatory for daily synchronization with local finance/ops teams; English (B2+) is required for technical documentation.
   

Nice to Have

• Background in FinTech, subscription models, payments, or high-volume e-commerce.
• Deep familiarity with Unity Catalog, Databricks Workflows, or Airflow.
• A strong track record of successful independent consulting engagements (references requested).