Head of Data Engineering

hace 2 días

Buenos Aires, Buenos Aires C.F., Argentina AstroPay A tiempo completo

Job Description
At AstroPay, we are transforming how decisions are made through data. As
Head of Data Engineering
, you will own the
data engineering vision, architecture, and execution strategy
, ensuring our data platform is scalable, reliable, cost-efficient, and aligned with business growth.

This role goes beyond hands-on development: you'll define the
data engineering roadmap
, lead and scale a high-performing team, and act as the bridge between business strategy, analytics, and engineering excellence. Your mission is to ensure that our data infrastructure consistently delivers trusted, high-impact data products across the organization.

Job Requirements
Must-Have

  • 8+ years of experience in Data Engineering, with proven ownership of large-scale data platforms.
  • Strong background designing and maintaining ETL pipelines and Data Lake architectures.
  • Advanced SQL expertise, particularly with BigQuery or similar big data technologies.
  • Strong proficiency in Python for data pipelines and automation.
  • Hands-on experience with relational and non-relational databases.
  • Proven experience leading and mentoring engineering teams.
  • Strong communication skills, with the ability to translate technical concepts to business stakeholders.

Nice to Have

  • Experience working in high-growth environments or startups.
  • A strong product mindset, understanding the "why" behind every data pipeline.
  • Experience enabling analytics, BI, and experimentation use cases.
  • Passion for continuous improvement and technical curiosity.

Job Responsibilities
Data Engineering Strategy & Architecture

  • Own the end-to-end data engineering strategy, aligning infrastructure decisions with business and product priorities.
  • Define and evolve the Data Lake / Data Platform architecture, ensuring scalability, reliability, and performance.
  • Evaluate, challenge, and improve existing data architectures, participating in high-level technical and strategic decisions.
  • Translate complex business needs into robust, long-term technical solutions.

Technical Leadership & Execution

  • Lead the execution of the data product and platform roadmap, coordinating priorities across teams.
  • Set engineering standards for ETL pipelines, data modeling, automation, and orchestration.
  • Oversee advanced SQL usage in BigQuery, ensuring efficient processing of large-scale datasets.
  • Drive best practices in Python-based data pipelines, automation, CI/CD, and GitHub workflows.

Team Leadership & Mentorship

  • Build, mentor, and scale a high-performing team of Data Engineers.
  • Act as a technical reference point, fostering a culture of engineering excellence, ownership, and continuous improvement.
  • Promote knowledge sharing, documentation, and sustainable development practices across the team.

Quality, Reliability & Efficiency

  • Ensure data quality, availability, and consistency across the platform.
  • Own SLAs, incident management, performance monitoring, and cost optimization.
  • Define and track engineering KPIs to guarantee reliability and efficiency at scale.

Cross-Functional Collaboration

  • Partner closely with Data Analytics, Product, Growth, and Engineering to enable trusted, analytics-ready data.
  • Ensure data infrastructure supports experimentation, reporting, and business intelligence needs.
  • Serve as a key stakeholder in company-wide discussions around data, scalability, and platform evolution.

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