Big Data Engineering Lead

Job not on LinkedIn

🕒 August 21

🇲🇽 Mexico – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

👻 Ghost score 43%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Sequoia Connect

WebsiteLinkedInAll Job Openings

11 - 50 employees

💼 Consulting

📣 Marketing

📦 Logistics

Consulting • Marketing • Logistics

Sequoia Connect is a company that specializes in IT advisory and talent services particularly focused on digital transformation. They provide headhunting services for technology specialists, IT consulting, and recruitment process outsourcing. With operations spread across multiple countries including the USA, Mexico, India, and regions in Latin America, they connect technologists with global companies. They aim to optimize processes, reduce operating costs, and maintain high standards of technological innovation. Sequoia Connect supports digital transformation for both multinational corporations and agile startups, serving over 700 clients across 50+ countries.

📋 Description

• Provide technical leadership, engineering delivery, and quality assurance for the Data Foundation platform • Lead the team building and maintaining enterprise data pipelines, data products, canonical data models, and data services • Enable analytics, AI, integration, and operational reporting through enterprise data solutions • Partner with the Service Owner, Architecture Team, and Platform Engineering Lead • Deliver scalable, trusted, and maintainable data solutions aligned with enterprise standards and strategic objectives • Take accountability for engineering execution, solution quality, operational reliability, and development of a high-performing data engineering team • Deliver Data Foundation engineering commitments • Ensure data pipeline reliability, performance, and scalability • Drive data quality improvements, adopt engineering standards, reduce technical debt, and improve operational stability • Increase reuse of canonical data models, data products, and engineering frameworks

🎯 Requirements

• 8+ years of experience in data engineering, software engineering, or enterprise data platform development • 3+ years of technical leadership experience leading engineering teams or large-scale data initiatives • Proven experience designing and delivering enterprise data platforms, pipelines, and data products • Experience operating within agile software development environments • Advanced SQL and data modeling expertise • Strong Python and PySpark development experience • Deep understanding of ETL and ELT architecture patterns • Strong technical leadership, coaching capabilities, and problem-solving skills • Resilience, emotional intelligence, and focus on agile delivery • Deep understanding of the difference between coding and engineering • Experience implementing Master Data Management solutions • Experience building RESTful APIs and data services • Familiarity with GraphQL and modern integration approaches • Understanding of microservices-based architectures • Experience implementing event-driven and real-time data processing solutions • Strong understanding of data quality frameworks, metadata management, and data lineage concepts • Familiarity with cloud-native foundations or AI coding assistants

🏖️ Benefits

• Flexible work arrangement with remote option • Continuous learning and professional growth opportunities • Exposure to high-impact projects and complex engineering challenges • International collaboration across a global network of expertise