T

Tiger Analytics

Delivers Data and AI transformation

Senior Data Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-timeRemote in USANo salary listed

About the Job

Requirements

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

Responsibilities

  • 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.

About the Company

Tiger Analytics

Delivers Data and AI transformation

Tiger Analytics helps large organizations plan and execute Data and AI–led transformations at scale. It works with clients to translate business needs into data and AI initiatives, using an approach that combines business value mapping, agile operating models, and a platforms-based architecture, backed by partnerships with major hyperscalers. The company designs and delivers end-to-end data and AI solutions—from strategy and data engineering to model development and deployment—so that AI can be applied to tough, real-world problems. Unlike firms that rely mainly on standard playbooks, Tiger Analytics builds custom approaches and accelerators to suit each client’s value chain and operating model. With a global team of 5000+ technologists and consultants, the goal is to enable measurable value and practical outcomes through data and AI programs that work at enterprise scale.

Company size
1,001-5,000
Company stage
Not listed
Total funding
Not listed
Headquarters
San Jose, CA
Founded
2010

Recently Posted Jobs

Explore more opportunities at Tiger Analytics

See more jobs