Data Engineering Lead

Job not on LinkedIn

🕒 March 18

🇲🇽 Mexico – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

👻 Ghost score 46%

What it means: the chance that no one is really hiring for this job.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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Tiger Analytics

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2011

🏥 Healthcare

📦 Logistics

📣 Marketing

Healthcare • Logistics • Marketing

Tiger Analytics is a leading AI and analytics consulting firm that specializes in leveraging data science and machine learning to provide strategic business insights across various industries. They offer services in data strategy, AI engineering, and business intelligence to enable data-driven decision-making and digital transformation for their clients. Tiger Analytics collaborates with top technology partners like Microsoft, Google Cloud, and AWS to deliver cutting-edge solutions. They serve a diverse range of sectors including consumer packaged goods, healthcare, and finance, helping businesses operationalize insights and differentiate with AI and machine learning technologies.

📋 Description

• Lead and manage data engineering projects from conception to deployment, ensuring alignment with stakeholder needs. • Design, build, and maintain scalable data pipelines to support data ingestion, transformation, and storage. • Collaborate with data scientists and analysts to ensure that data needs are met and provide technical guidance on best practices. • Implement and maintain data quality and integrity measures. • Utilize cloud-based data platforms and technologies, particularly Azure, to enhance data accessibility and usability. • Mentor and guide junior team members in data engineering concepts and practices. • Identify opportunities for process improvements and implement solutions that enhance efficiency, scalability, and performance.

🎯 Requirements

• 8+ years of experience in data engineering, with a proven track record of delivering scalable data solutions. • Strong expertise in cloud platforms (preferably Azure) and data processing technologies (e.g., Databricks, Spark). • Proficient in programming languages such as Python and SQL. • Experience in data modeling, ETL processes, and data warehousing. • Familiarity with machine learning concepts and integration of ML models into data pipelines is a plus. • Strong communication skills and the ability to work collaboratively with cross-functional teams. • Excellent problem-solving skills and a detail-oriented approach.

🏖️ Benefits

• A collaborative and innovative work environment. • Opportunities to work on impactful projects with global clients. • Competitive salary and benefits tailored to mid to senior professionals. • Continuous learning and career development opportunities. • Flexible working arrangements based in Mexico.

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