Big Data Lead/Mdm/Pyspark

Sequoia Connect LLC

Xico

A distancia

MXN 900.000 - 1.500.000

Jornada completa

Hace 7 días
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Descripción de la vacante

Sequoia Connect is seeking a Big Data Lead to drive technical leadership and delivery of a world-class Data Foundation. You will guide enterprise data pipelines, data products, and canonical models while advancing analytics, AI, and cloud-native solutions.

This is a remote role with exposure to a global engineering network and Fortune 500-scale challenges. You will mentor a high-performing data team, align with architecture and platform leads, and champion resilient, scalable data architectures.

Formación

  • Hands-on technical leader with enterprise data engineering expertise.
  • Strong background in modern data architectures, distributed processing and PySpark.
  • Solid understanding and hands-on experience with Master Data Management (MDM) principles.
  • Demonstrated ability to lead technical teams while remaining hands-on with pipelines and architectural design.
  • Exceptional communication skills to partner with cross-functional teams.
  • High-Performance Mindset with agile delivery.
  • Technologist DNA: understanding the difference between coding and engineering.

Responsabilidades

  • Provide technical leadership and ensure the quality of the Data Foundation platform.
  • Lead the team building enterprise data pipelines, data products, and canonical data models.
  • Enable advanced analytics, AI, and operational reporting through robust data architectures.
  • Collaborate with Service Owner, Architecture Team, and Platform Engineering Lead to deliver scalable data solutions.
  • Own engineering execution, solution quality, and operational reliability across the data platform.
  • Drive development, mentorship, and continuous improvement of the data engineering team.

Conocimientos

PySpark
MDM
Data pipelines
Data architecture
Cloud environments
Leadership
Cross-functional collaboration

Herramientas

Enterprise data platforms

Descripción del empleo

At Sequoia Connect, we are a Talent-First Technology Ecosystem that redefines how elite professionals interact with the global digital landscape. We move beyond traditional models to act as a catalyst for the top 1% of global talent, connecting human potential with complex industrial execution. By joining our inner circle, you are not simply taking a position; you are aligning with a strategic partner dedicated to updating your "Human OS" and accelerating your growth through world-class, high-impact projects.

We are currently partnering with a rapidly growing, automation-led powerhouse that serves 31 Fortune 500 companies across the financial, healthcare, and manufacturing sectors. With a global workforce of over 32,000 employees and a presence in 28 countries, our client is a titan of digital transformation. Their "Automate Everything, Cloudify Everything" strategy ensures you will be working at the absolute forefront of AI-driven automation and cloud solutions.

This is your chance to thrive in a "Customer Success, First and Always" environment that prizes continuous learning and radical ownership. You will collaborate within an international network of expertise across 39 delivery centers worldwide, gaining exposure to complex engineering challenges that redefine industrial standards. If you are a driven professional looking for a dynamic, forward-thinking workplace where your growth is the priority, this is where you belong.

We are currently searching for a Big Data Lead:

The Challenge (Responsibilities)
  • Provide technical leadership, engineering delivery, and ensure the overall quality of the Data Foundation platform.
  • Lead the team responsible for building and maintaining enterprise data pipelines, data products, canonical data models, and data services.
  • Enable advanced analytics, AI, system integration, and operational reporting through robust data architectures.
  • Partner closely with the Service Owner, Architecture Team, and Platform Engineering Lead to deliver scalable, trusted, and maintainable data solutions aligned with enterprise standards and strategic objectives.
  • Take accountability for engineering execution, solution quality, and operational reliability across the data platform.
  • Drive the development, mentorship, and continuous improvement of a high-performing data engineering team.
Your Profile (Requirements)
  • Proven experience as a hands-on technical leader with deep expertise in enterprise data engineering.
  • Strong background in modern data architectures, distributed processing, and engineering excellence (specifically utilizing PySpark).
  • Solid understanding and hands-on experience with Master Data Management (MDM) principles and canonical data models.
  • Demonstrated ability to lead technical teams while remaining hands-on with pipeline creation and architectural design.
  • Exceptional communication skills to partner seamlessly with cross-functional architecture and platform teams.
  • High-Performance Mindset: Resilience, emotional intelligence, and a focus on agile delivery.
  • Technologist DNA: A deep understanding of the difference between "coding" and "engineering."
Desired
  • Experience deploying data solutions within modern cloud environments (AWS, GCP, or Azure).
  • Familiarity with cloud-native foundations or AI coding assistants.
Languages
  • Advanced Oral English: For seamless collaboration with global teams.
  • Advanced Spanish.
Special Notes
  • Position ID: AR 681618
Work Arrangement

We value flexibility to support your lifestyle. This position is available as:

  • Remote

Keywords: Big Data, PySpark, MDM, Data Pipelines, Distributed Processing

  • Technical leadership, engineering delivery, and quality of the Data Foundation platform.
  • Lead team building enterprise data pipelines, data products, canonical data models, and data services.
  • Partner closely with Service Owner, Architecture Team, and Platform Engineering Lead.
  • Deliver scalable, trusted, and maintainable data solutions.
  • Hands-on technical leader with deep expertise in data engineering.
  • Expertise in modern data architectures, distributed processing, and engineering excellence.
  • Accountable for engineering execution, operational reliability, and team development.
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