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Tiger Analytics
Tiger Analytics
1,001 – 5,000 Employees
H1B Visa SponsorHealthcareLogisticsMarketing
Tiger Analytics is an AI and analytics consulting firm that helps organizations turn complex data into practical business decisions. Its work spans data strategy, machine learning, AI engineering, and business intelligence, with a focus on embedding analytics into day-to-day operations and broader digital transformation programs. The firm works across industries including healthcare, logistics, marketing, consumer goods, and finance, drawing on cloud technologies and partnerships with providers such as Microsoft, Google Cloud, and AWS to develop and scale data-driven solutions.
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Senior Data Engineer, Databricks and Spark

Build scalable data pipelines for Tiger Analytics’ enterprise clients using Databricks and Spark. Improve ETL workflows, batch scheduling, and production data solutions.

USUnited StatesTXTexasRemoteFull-timeSeniorEnglish RequiredData Engineer
ApacheETLHadoopPythonScalaSparkSQL

Description

  • Build and maintain scalable pipelines with Databricks, Spark, Python, and Scala.
  • Develop and improve ETL/ELT processes for ingesting, transforming, and processing data from varied sources.
  • Use Hadoop tools to process and manage large structured and unstructured datasets.
  • Tune and troubleshoot Spark applications to strengthen performance, scalability, and reliability.
  • Manage batch schedules, workflow dependencies, and pipeline runs with Control-M.
  • Investigate job failures and pipeline issues to keep scheduled workloads on time.
  • Add validation, error handling, and quality checks to maintain accurate, consistent data.
  • Partner with data architects, analysts, and other teams to gather needs and deliver dependable solutions.
  • Apply coding standards, testing practices, version control, and deployment procedures.
  • Support production releases, incident response, and ongoing solution maintenance.

Requirements

  • At least 8 years of data engineering experience.
  • Strong practical experience with Databricks and Apache Spark.
  • Proficiency in Python and Scala for data processing and application development.
  • Practical experience with Hadoop and big data technologies.
  • Experience using Control-M for batch scheduling, job monitoring, workflow orchestration, and dependency management.
  • Strong knowledge of ETL/ELT, data transformations, and distributed data processing.
  • Experience with performance tuning, debugging, troubleshooting, and production support.
  • Strong SQL skills and understanding of data management concepts.
  • Strong analytical, problem-solving, and collaboration skills.

Benefits

  • Medical coverage.
  • Dental coverage.
  • Vision coverage.
  • Retirement accounts.
  • Long- and short-term disability coverage.
  • Life insurance.
  • HSA/FSA accounts in the United States.
  • Discretionary time off.
  • Ongoing learning and practical exposure to emerging technologies.
  • Opportunities to develop expertise in generative AI, agentic AI, and next-generation data platforms.
  • Work with global AI, data, engineering, and consulting teams.
  • Opportunities to lead strategic engagements and develop client partnerships.

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