Big Data Engineering Lead

Job not on LinkedIn

🕒 August 20

🇲🇽 Mexico – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

👻 Ghost score 42%

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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VALCE Talent Solutions

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2016

🤝 B2B

🎯 Recruiter

💼 Consulting

B2B • Recruitment • Consulting

VALCE Talent Solutions is a company specializing in nearshoring, IT talent acquisition, and consultancy aimed at helping businesses expand globally, particularly in Mexico, LATAM, and the United States. They offer customized solutions that include talent recruitment, workforce management, and the integration of technology and artificial intelligence to enhance business processes. With a strong focus on strategic consulting, VALCE aims to connect technology, talent, and tangible results, boasting a robust network of IT professionals and a proven track record of successful placements and project scaling.

📋 Description

• Provide technical leadership for the engineering delivery and quality of 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 scalable 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 • Drive engineering execution, solution quality, operational reliability, and development of a high-performing data engineering team • Deliver Data Foundation engineering commitments • Improve data pipeline reliability, performance, and scalability • Improve data quality across enterprise data assets • Promote engineering standards and development practices • Reduce technical debt and engineering risk • Improve operational stability and reduce incidents • Support engineering team engagement, capability growth, and retention • 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 • 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 • Advanced English • Strong technical leadership and coaching capabilities • Excellent problem-solving and decision-making skills • Ability to balance delivery commitments with long-term platform sustainability • Strong collaboration and stakeholder engagement skills • Excellent written and verbal communication abilities • Passion for engineering excellence and continuous improvement

🏖️ Benefits

• No benefits or compensation extras explicitly stated