Experience & Competencies: Previously worked closely with data architect or data modellers, can independently work on data analysis, data modelling. Proficient in manipulating data and drawing insights from large data sets using SQL Highly proficient in data preparation and integration, able to design, develop and modify data models and troubleshoot performance issues. Good in doing downstream analysis and understanding end to end data flow when multiple systems are involved. Experienced with working on Agile delivery. Expected to have strong at least 3 to 4 years of hands-on experience in SQL. Familiarity with data governance, data quality and control frameworks would certainly be useful in this role. Able to creatively use data and insights to uncover new opportunities, identify root causes and underlying risks to recommend solutions to the business. Technical Skills: Advanced data engineering skills with strong experience using Spark, SQL, Python and Airflow Strong knowledge of big data querying tools such as Presto or Trino. Experience in data architecture principles, including data access patterns and data modelling. Experience with data quality measurement and monitoring Experience with metadata, including control totals and check sums for load assurance. Comfortable taking ownership of issues and driving resolution. Familiar with cloud computing concepts (AWS) including any or all of EC2, S3, IAM, EKS and RDS and Linux Good understanding of Data Warehousing/ETL concepts Experience with CI/CD tools Experienced with DevOps approaches
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