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Odysseus Data Services, UAB
Big Data Engineer / ETL Engineer
Odysseus Data Services, UAB
Odysseus Data Services, UAB

Big Data Engineer / ETL Engineer

Odysseus Data Services, UAB

Odysseus provides services which require highly specialized skills:

  • Data manipulation and transformation into the OMOP Common Data Model
  • Medical coding, mapping and management of complex medical vocabularies
  • Experience with country-specific features and conventions
  • Software product development on the basis of observational patient data, especially in the OHDSI platform

Odysseus team interacts directly with the experts from Observational Health Data Sciences and Informatics (OHDSI) collaborative and complementing them with the team of seasoned software engineers.

Responsibilities
• Data Management and Big Data Engineering e.g. complex ETL, data analysis, data mappings, advanced transformations

• Architect and utilize Big Data Platforms for Big Data projects

• Develop solutions in Agile fashion following Scrum process and Test-Driven approach enabled with Atlassian tools (JIRA, Confluence)

• Develop solutions by applying industry best practices and coding standards

• Document architecture design by creating necessary architecture artifacts, including UML domain models, component and deployment diagrams. Document business requirements as user stories

• Create prototypes and POCs, as needed

• Design secure and compliant solutions by implementing necessary application security and following various regulatory laws (HIPAA, GDPR)

• Be a part of the dynamic open-source observational research OHDSI community, participate in workshops, hackathons and collaborate to implement observational research solutions e.g. have a fun time developing cutting-edge solutions

Required Skills

• Bachelor’s or Master’s degree in Information Technology or Computer Science — or equivalent experience in information technology and software development

• Complex SQL, including Spark SQL, Hive QL

• Practical experience with ETL and big data processing

• Practical experience with RDBMS (any of the following - Oracle, PostgreSQL, SQL Server)

• Practical experience with MPP databases (any of the following - AWS RedShift, BigQuery, Synapse)

• Practical experience with Hadoop e.g. Spark, Hive, Impala

• Practical experience with one of the following platforms: AWS, GCP and Cloudera

• Experience designing and developing solutions using Agile software development approach

Desired Skills

• Experience in administering the Big Data platform infrastructure

• Knowledge of Java and Python

• Experience in solving DevOps-related tasks

• Experience with OMOP CDM, OMOP Standardized Vocabularies, methods and standards developed by OHDSI community

What we offer

• An attractive work/life balance (40-hours per week)
• Comfortable office with all amenities
• Official employment in accordance with the legislation of Lithuania.
• Competitive salary
• Paid vacation and sick leave
• Free language courses

Mėnesinis bruto atlyginimasBruto/mėn.  € 2500

Papildoma informacija: Salary: from 2500 euro gross (discussed individually)

Vietovė

    Vilnius, Vilniaus apskritis, Lietuva
    Office location: room 001, Vytenio gatvė 9, LT-03113 Vilnius

Laikas

  • Visa darbo diena
  • Lankstus grafikas

Įgūdžiai

 Big Data  • Complex SQL Spark SQL Hive QL RDBMS Oracle PostgreSQL Agile AWS Spark Synapse BigQuery SQL Server

Kalbos

  •  Anglų
Kontaktinis asmuo
Svetlana Ilyankova

Join us in our journey!

Odysseus Data Services (https://odysseusinc.com/) - is a fast-growing US-based company focused on the creation of a single platform that will combine medical history data from clinics all over the world. Our goal is to provide a vast information base to be used by scientific researchers, medical centers and institutes, as well as the pharmaceutical industry and insurance companies.

Today Odysseus Data Services is an active member of the Observational Health Data Sciences and Informatics (or OHDSI, pronounced "Odyssey") consortium (https://www.ohdsi.org/ ), whose main mission is to improve health care systems around the world by collecting and organizing data on the treatment of various diseases and then combining this data into a single, standardized, universally-accessible knowledge base to bring out the value of health data through large-scale analytics.


Įmonės tinklalapishttps://odysseusinc.com