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Data Engineer

Description

Role

  • Diagnose existing architecture and assess data utility; identify gaps 
  • Lead feature engineering and DS pipeline creation, including ETL experience and support for DS feature selection efforts
  • Design and jointly develop the data architecture with data architect; ensure scalability, security and maintenance
  • Build data tools and products for effort automation and easy data accessibility

 Responsibilities

  • Collaborate with Data Architect to execute tasks within agreed framework and with 
  • Collaborates with Product Owner to deliver solutions that avoid unnecessary changes in the future
  • Gathers requirements, assesses gaps and builds roadmaps and architectures to help the analytics driven organization achieve its goals
  • Works closely with Data Analysts to ensure data quality and availability for analytical modelling
  • Explores suitable options, designs, and creates data pipeline (data lake / data warehouses) for specific analytical solutions
  • Defines ETL / ELT based on jointly defined requirements
  • Orchestrates pipeline and queries with sequence of imports
  • Identifies gaps and implements solutions for data security, quality and automation of processes
  • Support maintenance, bug fixing and performance analysis along data pipeline based on a TCO approach
  • Collaborates with business and understands UC application of data


Technical Skills

  • BS/MS degree in Computer Science, Engineering, background in Mathematics and Statistics is good to have
  • At least 6 years of experience in Data Engineering Domain.
  • Ability to write clean code and documentation, optimize code, and reduce infrastructure cost
  • Data manipulation and munging in Python, incl. at scale e.g., PySpark or a similar language
  • Experience on cloud infrastructure (e.g., Microsoft Azure, Databricks)
  • Experience using SQL, PL/SQL or T-SQL with RDBMSs like Teradata, MS SQL Server, Oracle etc in production environments is a plus.
  • Experience in data engineering & data bases/warehouses
  • Experience on Big Data platforms (e.g. Hadoop, Map/Reduce, Spark, HBase, CouchDB, Hive) preferred 
  • Experience with BI and data visualization packages is a plus
  • Comfort with shell scripting (e.g., Bash) and Python (or similar) scripting
  • Business acumen and ability to communicate technical matters to non-experts.
  • Some hands-on experience in data structuring / cleaning, creating data pipelines, and agile
  • Independently executes data engineering projects

Equality

All qualified applicants will receive consideration for employment without regard to age, disability or medical condition; colour, ethnicity, race, citizenship, and national origin; religion; pregnancy, family status and caring responsibilities; sexual orientation; sex, gender identity, gender expression, and transgender identity; protected veteran status; size or any other basis protected by appropriate law. 

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