Data Engineer
The Judge Group Inc.

Denver, Colorado

Location: Denver, CO
Description: Overview of the role The Data Solution Architect will play a key role in DTE, working closely with the Strategic Data Platform team and other data providers to make data available for the DTE team for use in dashboards and APIs.

Duties and responsibilities You will: Distribution Technology Enterprise -

  • work with various data owners and SMEs from other teams to understand various financial datasets, their architecture, dependencies, flow and business use cases, then model these datasets to make available for downstream use by the Distribution Enterprise Team.
  • Assist if needed, to normalize and migrate datasets into the global dimensional database in Databricks, build reporting / analytics datasets in Snowflake, review and refine their logical and physical data models and ensure that the API endpoints support the requirements of consumers.
  • Work with Distribution & Corporate Technology (DCT) Data Providers and help make DCT owned data available for consumption by DTE as appropriate.
  • Engage with core Data Architecture Team to align Distribution Technology Enterprise (DTE) activities with data architecture principles and patterns and contribute to the evolution of these based on practical experience Engage with the Core Cloud Platform and Dev Ops / API development teams to help align DTE activities with strategic technology choices, patterns and practices Engage with Enterprise Data Management to ensure that DTE activities align with data governance objectives and that project and product teams are supporting required cataloging and glossary preparation activities as an enabler to ongoing data quality management Ensure DTE teams engage with Information Security to ensure appropriate data access and permissions are defined Documentation -
  • maintain a Confluence site providing how-to guides and signposts to other data architecture / data design resources Technical skills and qualifications Proven experience in architecting and implementing Business Intelligence and data warehouse platforms, Master Data Management, data integration and OLTP database solutions
  • Experience with Python, Spark, or other similar programming language Strong knowledge of industry best practices around data architecture in both cloud based and on-prem solutions.
  • Strong analytical and numerical skills are essential, enabling easy interpretation and analysis of large volumes of data
  • A comprehensive understanding of the principles of and best practices behind data engineering, and the supporting technologies such as RDBMS, NoSQL, Cache & In-memory stores Experience of architecting data solutions across hybrid (Azure cloud, on premise) data platforms Experience with Azure technologies like Databricks, Cosmos Experience with tools like snowflake and Power BI A comprehensive understanding of data warehousing and data transformation (extract, transform and load) processes & the supporting technologies such as Azure Data Factory, python based ETL, Data Lake & other analytics products
  • Experience of using an enterprise data modelling tool such as ER/Studio Experience of mapping key Enterprise data entities to business capabilities and applications Experience dealing with multiple huge datasets to get meaningful results
  • A strong knowledge of horizontal data lineage from source to output and a good appreciation of the role of data governance in successful implementations Experience in systems which integrate with a data lake following a hub and spoke model using API,
  • messaging and batch ETL technologies In depth experience working in an agile environment Experience in Asset Management, Wealth Management or Investment Banking is preferred


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