Data Analyst ETL Developer at Remote, Remote, USA |
Email: [email protected] |
From: vivek, vyzeinc [email protected] Reply to: [email protected] Data Analyst/ETL Developer Hybrid-Lansing, Michigan Any Visa Skype JD POSITION DESCRIPTION: As a Data Analyst/ETL Developer within the Office of Retirement Services (ORS), you will play a vital role in managing and optimizing the data infrastructure, ensuring data quality, and facilitating effective data migration efforts. You will work as a contractor, collaborating closely with internal stakeholders and technical teams to support ORS's data-related initiatives, especially in the context of our ambitious modernization effort, using Agile methodologies, to update our current 17-year-old software package, to a modernized new product for the future. KEY RESPONSIBILITIES: Data Profiling and Source-to-Target Mapping: Lead data profiling and source-to-target mapping exercises to understand data sources, structures, and relationships. Root-Cause Analysis: Oversee the identification and resolution of data irregularities by conducting root-cause analyses and implementing approved solutions. Requirements Gathering: Engage with customers and business partners to gather data-related requirements, ensuring alignment with ORS objectives. SQL Expertise: Demonstrate strong SQL skills, particularly with Microsoft SQL Server, to manipulate, query, and transform data effectively. Data Integration Workflow Design: Leverage multiple years of experience to design complex data integration workflows that support ORS's data needs. Data Migration Leadership: Lead data migration efforts, with preference given to experience in migrating from on-prem data solutions to cloud databases. Modernization Effort: Play a key role in our ongoing modernization effort to replace our aging software, which is over 17 years old, with a new, modern system coded up to current standards. Contribute to the development of this cutting-edge software, ensuring that the data integration and ETL processes are aligned with our modernization goals. Agile Methodology: Embrace our recent transition from Waterfall to Agile software methodology, participating actively in Agile development practices, including sprint planning, stand-up meetings, and iterative development. Industry Best Practices: Stay informed about industry best practices and standards, advocating for and implementing data-driven solutions that maximize efficiency and quality. Problem-Solving Skills: Ability to think abstractly and break down complex data issues and solutions into simplified, actionable tasks. Mentorship: Provide guidance and mentorship to first-time developers in data profiling and source-to-target mapping exercises. Data Management Knowledge: Display familiarity with key data management concepts, including Master Data Management, Data Quality Management, Metadata Management, Data Security, Information Lifecycle Management, and Data Governance. Keywords: |
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Thu Nov 02 03:57:00 UTC 2023 |