Tiger Analytics
Tiger Analytics
Tiger Analytics ir mākslīgā intelekta un analītikas konsultāciju uzņēmums, kas palīdz organizācijām pārvērst sarežģītus datus praktiskos biznesa lēmumos. Uzņēmuma darbība aptver datu stratēģiju, mašīnmācīšanos, mākslīgā intelekta inženieriju un biznesa informācijas analīzi, īpašu uzmanību pievēršot analītikas integrēšanai ikdienas darbībā un plašākās digitālās pārveides programmās. Uzņēmums darbojas veselības aprūpes, loģistikas, mārketinga, patēriņa preču un finanšu nozarēs, izmantojot mākoņtehnoloģijas un sadarbojoties ar tādiem pakalpojumu sniedzējiem kā Microsoft, Google Cloud un AWS, lai izstrādātu un mērogotu uz datiem balstītus risinājumus.

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.

Apraksts

  • 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.

Prasības

  • 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.

Priekšrocības

  • 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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