Senior Data Engineer

🕒 October 15

🏖️ New Jersey – Remote

🏖️ New Jersey – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 11%

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

• Design, develop, and maintain scalable data pipelines using Azure data services, Python, Scala, and Apache Spark. • Develop and optimize ETL/ELT processes for data ingestion, transformation, and processing across diverse data sources. • Build and manage data pipelines using Azure Data Factory, Azure Databricks, and Azure Data Lake Storage. • Develop and optimize Spark applications to improve data processing performance, scalability, and reliability. • Work with Hadoop and related big data technologies where applicable. • Monitor pipeline execution, troubleshoot failures, and resolve data processing issues to ensure reliable data delivery. • Implement data validation, error handling, and data quality checks to ensure accuracy and consistency. • Collaborate with data architects, analysts, and cross-functional teams to understand requirements and deliver reliable data solutions. • Follow coding standards, testing practices, version control, and CI/CD procedures. • Support production deployments, incident resolution, performance tuning, and ongoing maintenance of data engineering solutions.

🎯 Requirements

• Bachelor’s degree in Computer Science, Information Technology, Computer Engineering, or a related field. • 10+ years of overall Data Engineering experience. • Strong hands-on experience with Microsoft Azure data services, particularly Azure Data Factory, Azure Databricks, and Azure Data Lake Storage. • Proficiency in Python and Scala for data processing and application development. • Strong experience with Apache Spark and distributed data processing. • Hands-on experience with Hadoop and big data technologies. • Strong understanding of ETL/ELT processes, data transformations, and data pipeline architecture. • Strong SQL skills and experience with performance tuning, debugging, troubleshooting, and production support. • Experience with Control-M for batch scheduling, job monitoring, workflow orchestration, and dependency management. • Familiarity with version control, CI/CD, and deployment practices. • Excellent analytical, problem-solving, and collaboration skills.

🏖️ Benefits

• Medical, Dental, Vision • Retirement Accounts • Long and Short Term Disability • Life Insurance • HSA/FSA Accounts (USA) • Discretionary time-off • Strategic engagements involving enterprise-wide AI adoption, cloud-native data modernization, and measurable business outcomes • Collaboration with AI, data, engineering, and consulting talent across geographies • Continuous learning and hands-on exposure to emerging technologies • Opportunities to build expertise in Generative AI, agentic AI, and next-generation data platforms • Opportunities to grow strategic client partnerships • Equal employment opportunities

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