NHS Human Services, Inc.

This is a contract with a great organization. As a contractor for Smith Johnson, you are eligible for medical, dental, life, disability. Smith Johnson pays for 70% of your medical and dental and 100% of life and disability. The contract is also eligible for PTO/holiday accrued monthly. You are also eligible for a 3% retirement matching plan. Smith Johnson believes in taking care of our contractors.

Summary:

Our client is working on a comprehensive modernization initiative, replacing a current legacy system data collection and associated reporting applications and reports from the ground up. We are looking for a highenergy, adaptive team player with a great work ethic to join our IT team as a Data Engineer to be accountable for the architecting and solutioning of our data pipeline.

The Ideal Candidate:

The ideal candidate for this position has experience in Azure, data pipelines, data architecture and warehousing, and has dabbled in machine learning. They are a Data Engineer with a passion for data, and for making peoples' lives easier. They enjoy both philosophical discussions and physical deployments and are comfortable working with multiple teams.

Principal Duties:

• Develop and maintain scalable data pipelines and build out new API integrations to support continuing increases in data volume and complexity
• Design efficient data structures and database schemas, as well as work with distributed system architecture and non-relational databases
• Collaborate with analytics and business teams to improve data models that feed business intelligence tools, increasing data accessibility and fostering data-driven decision making across the organization
• Implement processes and systems to monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it
• Perform data analysis required to troubleshoot data related issues and assist in the resolution of data issues
• Work closely with a team of engineers, product managers, and analysts
• Define company data assets (data models), jobs to populate data models
• Design data integrations and data quality framework
• Design and evaluate open source and vendor tools for data lineage
• Work closely with all business units and engineering teams to develop strategy for long term data platform architecture
• Other duties as assigned

Requirements:

• Bachelor degree from an accredited college in Computer Science, Information Technology, Business, or equivalent experience
• 5+ years of experience with BI reporting tools like Power BI or Tableau
• 3+ years of experience with large sets of regulated data, designing efficient data structures, and database schemas, as well as working with distributed systems architecture and CosmosDB
• 3+ years of experience with SQL and Python, with a focus on building reusable frameworks
• 3+ years' experience with integration technologies and protocols such as SOAP, REST, JSON and APIs, with experience in handling streaming data
• Experience with planning and implementing a data warehouse, data lake, or other data repositories is required
• Hands-on experience in Azure Data Factory, DataBricks, Azure Storage, SQL Pools, CI/CD Pipeline Design along with other Azure services like functions and Logic apps
• Ability to work well with others of all personality types while demonstrating problem-solving and the ability to prioritize tasks
• Ability to communicate in verbal and written form with both technical and non-technical personnel
• Demonstrate success as a self-starting, hardworking and inquisitive worker
• Demonstrate the ability to work with cross-functional teams to deliver on a common goal
• Demonstrate experience in an agile product environment to include deep understanding and experience with agile methodologies

Bonus skills:

• Azure Data Engineering, Azure DBA, Azure Developer or other related certifications
• Understanding and experience with Domain Driven Design
• Financial or Education Domains and their data standards -- Ed-Fi, CEDS, SIF, GAAP, etc.
• Knowledge and Experience with Data Privacy, Data Governance, and Data Cataloguing principles
• Knowledge of best practices and experience with Machine Learning