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Data Engineer

posted by: spj_bot

Tiger Analytics is a fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best analytics global consulting team in the world.

We are seeking an experienced Data Engineer to join our team, specifically focused on building scalable Generative AI architectures within the AWS ecosystem. You will architect the data foundations that power LLMs and autonomous agents for our Fortune 500 partners.

Requirements

  • Experience: 8-12 years in Data Engineering with a heavy focus on the AWS Cloud stack.
  • AWS Expertise: Deep hands-on experience with Glue, Athena, EMR, and Redshift.
  • AI/ML Tools: Proficiency in LangChain or LlamaIndex integrated with AWS services to handle unstructured data (text, images, PDFs).
  • DevOps & IAC: Experience deploying infrastructure using AWS CDK or Terraform.
  • Core Skills: Advanced SQL, Python and PySpark skills tailored for distributed processing on AWS.

Benefits

Job Skills

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Cloud Data Architect

posted by: spj_bot

Tiger Analytics is an advanced analytics consulting firm. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our consultants bring deep expertise in Data Science, Machine Learning, and AI. Our business value and leadership have been recognized by various market research firms, including Forrester and Gartner. We are one of the highest-rated employers on Glassdoor.

If you are passionate to work on unstructured business problems that can be solved using data, we would like to talk to you.

Job Skills

datasets leadership mentorship data warehouse automation data data ul information system data integration data data lakes data engineer frameworks spark on prem GCP resiliency big datum cloud security sql computer science production management data quality load balancers nosql stream processing consultants bigquery management process career development data ingestion manage production python operationalizing data lake cloud azure data engineers best practices storage analytics programming languages flink communication skills kubernetes scala communicate redshift data science market research professional certification consulting accounts devops scrum machine learning metadata snowflake mitigate firewalls scale coordinate improve productivity system administration java transformation agile methodology
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