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Job Post
Avinity Analytics

Data Engineer

Avinity Analytics Posted: 2 Month
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Description:
  • Responsibilities

  • Create and maintain optimal data pipeline architecture via scheduling and authoring tools such as Airflow & dbt.
  • Wrangling large, complex data sets that meet functional / non-functional business requirements.
  • Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability.
  • Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL including Google, Microsoft & AWS cloud data/serverless technologies.
  • Build analytics models that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
  • Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
  • Qualifications

  • Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as query optimisation.
  • Strong analytic skills related to working familiarity with a variety of databases - MSSQL, MySQL, PostgreSQL, MongoDB.
  • Build processes supporting data transformation, data structures, metadata, dependency and workload management.
  • A successful history of manipulating, processing and extracting value from large disconnected datasets.
  • Knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
  • Strong project management and organizational skills.
  • Experience supporting and working with cross-functional teams in a dynamic environment.
  • We are looking for a candidate with 1+ years of experience in a Data Engineer / Database Management / Backend Developer role, who has attained a Graduate or higher degree in Software Engineering, Computer Science, Statistics, Informatics, Information Systems or another quantitative field. They should also have experience using some of the following software/tools:
  • Experience with big data storage & transform tools: Hadoop, Spark, Kafka, Snowflake, BigQuery.
  • Experience with relational SQL and NoSQL databases.
  • Experience with data pipeline and workflow management tools: Luigi, Airflow.
  • Experience with AWS cloud services: EC2, Labda, EMR, RDS, Redshift
  • Experience with stream-processing systems: Kafka, Spark-Streaming, etc.
  • Experience with object-oriented/object function scripting languages: Python, Java, C++, Javascript, R.

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