Data Analyst, II - Utility experience required at VertexOne

Job description

Data Analyst II, Data Migration Job Description Overview of Role/Job Purpose: The Data Analyst II, Data Migration is a highly visibility role focused on migrating and onboarding utility customers to VertexOne's CIS platform. Reporting to the Data Migration Manager, this analyst extracts, profiles, maps, transforms, and validates customer data from legacy systems. They ensure data accuracy, conversion stability, and clear exceptions handling through every phase of delivery. The role combines analytical judgement with practical automation and process improvement. This person will help improve the way we deliver migrations so that each conversion is more repeatable, efficient, and reliable. They will work closely with internal teams and utility clients during discovery, mapping, mock conversions, validation, and go-live. The successful candidate is deeply data driven, meticulous, and able to communicate complex data issues clearly to both technical and business audiences. They will partner closely with the Data Migration Manager on delivery planning, team direction, and practical AI automation, and act as the manager's delegate when needed. This is a hands-on role for someone who is technology-curious, eager to learn, enjoys solving messy data problems, building practical expertise, and growing into team leadership within the data migration organization. Essential Duties: Work with clients to extract, profile, and analyze source data from legacy utility CIS, billing, and metering systems, including relational databases, and flat or fixed width files. Lead day-to-day technical direction for migration engineers, including reviewing and approving mappings, transformation logic, and validation results before they go to clients. Create and maintain project and team weekly status reports. Develop and maintain source to target data mappings and transformation logic in partnership with Implementation, Product, and utility client teams. Write, optimize, and maintain SQL for data extraction, transformation, reconciliation, and validation. Execute mock conversions and production cutovers, validating record counts, balances, and business rules at each migration phase. Own cutover readiness for assigned client migrations, including runbooks, go/no-go recommendations, and post-migration validation sign-off. Design and implement data quality checks, reconciliation reports, and exception handling that surface issues early and ensure stability through go live. Identify manual and repetitive migration tasks and build automated, reusable workflows using KNIME, scripting, and other automation tooling. Contribute to the continuous improvement of migration methodology, templates, and standards to increase accuracy, efficiency, and repeatability. Perform root cause analysis on data defects and conversion errors, and drive resolution with internal and client stakeholders. Own one or more client migration streams end to end and act as interim decision-maker when the Data Migration Manager is unavailable. Lead data and migration training sessions for clients, explaining utilities CIS data entities and relationships, including functional concepts on how they relate to each other. Communicate migration status, data quality findings, risks, and readiness clearly to project teams, leadership, and utility clients. Document mappings, processes, workflows, and lessons learned for internal knowledge sharing. Uphold data governance, privacy, and security standards for sensitive customer and billing data. Job Qualifications: 4 to 8 years of experience in data analysis, data migration, ETL, or a related technical role. Experience leading or reviewing the work of other analysts or engineers on data migration or ETL projects. Strong proficiency in SQL, including complex joins, aggregations, and data validation queries. Experience with utility CIS or billing platforms (e.g., SAP IS-U, Oracle CC&B, or similar) and utility meter or billing data. Demonstrated experience with data mapping, data profiling, and data quality or reconciliation practices. Experience with ETL or workflow tools (e.g., KNIME, SSIS, Talend, Alteryx, Airflow, Python). Exceptional attention to detail and a data driven approach to problem solving and decision making. Ability to manage multiple migration workstreams and deadlines in a fast paced, high visibility environment. Excellent written and verbal communication skills, with the ability to explain technical findings to business and client audiences. Flexibility to work occasional evenings and weekends during production cutovers and go live events. Coordinate with an offshore delivery team, including regular working-hour overlap. Preferred Qualifications: Bachelor’s degree in Information Systems, Computer Science, Data Analytics, or a related field. Hands-on SQL experience with DB2 for IBM i (AS400) or other legacy mainframe data sources. Experience with KNIME Analytics Platform. Proficiency in Python or another modern programming language for data processing and automation. Experience with agentic engineering, including using AI agents and LLM tools to accelerate analysis, mapping, and automation. Familiarity with automation and orchestration tooling (e.g., Airflow, Bash scripting, CI/CD pipelines) and version control (e.g., Git). Experience in a SaaS organization. Personal Attributes: Meticulous: Treats every record as important and holds a high bar for accuracy and completeness. Data Driven: Relies on evidence, metrics, and validation results to guide decisions and recommendations. Process Improver: Continuously looks for ways to automate, standardize, and strengthen how work gets done. Clear Communicator: Conveys status, risks, and findings with clarity and confidence to technical, business, and client audiences. Composed Under Pressure: Stays steady and focused during cutovers, tight deadlines, and high visibility moments. Collaborative: Builds trust across Implementation, Product, Engineering, and client teams. Ownership Minded: Takes accountability for deliverables from mapping through go live.

Requirements

Must-haves

Data Analyst II, Data Migration
Work with clients to extract, profile, and analyze source data from legacy utility CIS, billing, and metering systems, including relational databases, and flat or fixed width files.
Lead day-to-day technical direction for migration engineers, including reviewing and approving mappings, transformation logic, and validation results before they go to clients.
Create and maintain project and team weekly status reports.
Develop and maintain source to target data mappings and transformation logic in partnership with Implementation, Product, and utility client teams.
Write, optimize, and maintain SQL for data extraction, transformation, reconciliation, and validation.
Execute mock conversions and production cutovers, validating record counts, balances, and business rules at each migration phase.
Own cutover readiness for assigned client migrations, including runbooks, go/no-go recommendations, and post-migration validation sign-off.
Design and implement data quality checks, reconciliation reports, and exception handling that surface issues early and ensure stability through go live.
Identify manual and repetitive migration tasks and build automated, reusable workflows using KNIME, scripting, and other automation tooling.
Contribute to the continuous improvement of migration methodology, templates, and standards to increase accuracy, efficiency, and repeatability.
Perform root cause analysis on data defects and conversion errors, and drive resolution with internal and client stakeholders.
Own one or more client migration streams end to end and act as interim decision-maker when the Data Migration Manager is unavailable.
Lead data and migration training sessions for clients, explaining utilities CIS data entities and relationships, including functional concepts on how they relate to each other.
Communicate migration status, data quality findings, risks, and readiness clearly to project teams, leadership, and utility clients.
Document mappings, processes, workflows, and lessons learned for internal knowledge sharing.
Uphold data governance, privacy, and security standards for sensitive customer and billing data.

Nice-to-haves

Bachelor’s degree in Information Systems, Computer Science, Data Analytics, or a related field.
Hands-on SQL experience with DB2 for IBM i (AS400) or other legacy mainframe data sources.
Experience with KNIME Analytics Platform.
Proficiency in Python or another modern programming language for data processing and automation.
Experience with agentic engineering, including using AI agents and LLM tools to accelerate analysis, mapping, and automation.
Familiarity with automation and orchestration tooling (e.g., Airflow, Bash scripting, CI/CD pipelines) and version control (e.g., Git).
Experience in a SaaS organization.

Application prep

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Keywords to mirror

goaisqlpythonllmci/cd

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