The Data Engineer will perform the following job duties:

Collaborate with a multi-disciplinary team of solution architects, engineers, and data scientists on a wide range of business problems. Responsible for building out capabilities and service offerings across business strategy, Big Data/analytics, and Cloud. Work with account teams to sell and deliver solutions to customers. Provide big data solutions to a wide range of Fortune 200 customers in oil and gas, mining, healthcare, financial services, and retail industries.

Design and develop data pipelines on data-heavy tech environments (data warehouse, ETL, and BI tools). Partner with data architects, data scientists, domain experts, data analysts, and other teams to build foundational data sets that are trusted, well understood, aligned with business strategy, and enable self-service. Manage the overall strategy for data governance, security, privacy, quality, and retention that will satisfy business policies and requirements. Own and document data pipelines and data lineage.

This position is 100% remote and can be performed from any home office in the United States. The position reports to Headquarters in Maryland Heights, Missouri. 20% domestic travel to client locations for kickoffs, on site work, and project closeouts. The requirements for the above-referenced position include:

Masters degree in Computer Science, Information Systems, or a related academic field, plus 2 years of experience as a data engineer or in any occupation in which the experience was gained, plus demonstrated experience in:

Design cloud-based Data Lakes, Analytics Platforms, and Warehouse diagrams using Lucidchart or Draw.io to show dataflow, networking, Cloud Account Management, security and access, system interaction, and SLAs;

Create a PowerPoint presentation for CTOs showcasing how the Data Lake, Analytics Platforms, and Warehouse designs drive business value in terms of working efficiency, revenue generated, and costs saved;

Deploy all components of the cloud-based Data Lakes, Analytics Platforms, and Warehouses using Terraform, AWS CloudFormation, or Azure Resource Manage;

Working with sales teams as a technical advisor to provide technical input on potential projects helping determine the level of effort and complexity;

Collaborating with data scientists, software engineers, data analytics, and other domain experts to build foundational data sets that are trusted, well understood, aligned with business strategy, and enable self-service

;

Collaborating with customers project managers and development teams to ensure the customers are kept informed of ongoing engineering efforts and that the customers engineers can continue to work once you leave the project;

Building data pipelines that move data from source systems to a target database while performing data transformations, data quality checks, and data validations;

Modeling Kimball dimensional data models in SQL for relational databases;

Modeling OLAP data models for AWS Redshift, Snowflake, Azure Analysis Services, or Databricks;

Building data pipelines in Python and SQL using Apache Spark, Azure Data Factory, Fivetran, AWS Glue, AWS Lambda, Azure Functions, or Google Cloud Functions;

Developing reports on top of analytical and transactional databases using Tableau or PowerBI;

Documenting database schemas and pipeline logic using markdown in git repositories and Atlassian Confluence.

WORLD WIDE TECHNOLOGY HOLDING CO LLC

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Data Engineer