Data Mapping and Schema Analyst

Drone.vet; Portland (OR); Hybrid; USD 83,000 - 96,000; Part time

Benefits offered by this job

Medical, Vision, and Dental Insurance

401k Retirement Fund

Job summary

Drone.vet in Portland, OR, is seeking a data migration analyst to map legacy inspection and correction data to a new database model and oversee accurate ingestion. You will analyze multiple source systems, identify data types, relationships, and dependencies to guide conversion.

Collaborating with business users, DBAs, data engineers, and project teams, you will document mappings, data dictionaries, and validation criteria, resolve data quality issues, and ensure data meaning is preserved during

Qualifications

• Five+ years of experience with databases, data analysis, data mapping, data conversion, schema analysis, or application data support.
• Experience analyzing relational databases and writing SQL queries to research tables, fields, joins, dependencies, and data quality issues.
• Experience creating source-to-target mapping documentation, data dictionaries, table inventories, or conversion specifications.
• Experience working across multiple business systems or legacy applications to understand data lineage, operational processes, and system-of-record decisions.
• Strong collaboration and communication with stakeholders in technical and nontechnical contexts.

Responsibilities

• Perform detailed analysis of inspection and correction data across multiple source systems, databases, and applications to understand how data is structured, stored, maintained, and used by the business.
• Research source databases and system tables to identify table names, field names, relationships, data types, key values, and data dependencies needed to support data conversion and migration work.
• Create clear source-to-target data mappings that align legacy inspection and correction data to the new data model, schema, and ingestion requirements for a modernized database environment.
• Work closely with business stakeholders, application teams, database administrators, data engineers, and project teams to validate data definitions, resolve mapping questions, and ensure data meaning is preserved during conversion.
• Identify data gaps, inconsistencies, duplicates, and quality issues that could impact successful ingestion into the new database, and document recommended remediation steps.
• Translate business rules and operational inspection/correction processes into technical data requirements, including mapping logic, transformation rules, and validation criteria.
• Develop and maintain detailed documentation, including data dictionaries, table inventories, mapping workbooks, schema alignment notes, conversion assumptions, and open data issues.
• Support data conversion planning, mock loads, validation activities, and issue resolution to help ensure inspection and correction data is accurately prepared for ingestion into the new database.
• Work independently with strong attention to detail and follow through on complex data research assignments with minimal guidance.
• Act as a knowledgeable resource for project team members by explaining source-system data structures, data lineage, table relationships, and conversion impacts.

Skills

Relational databases

Strong SQL skills

Data modeling

Data mapping

Data transformation

Data ingestion

Documentation

Communication

Problem-solving

Attention to detail

Collaboration

Education

Bachelor's degree in computer science, information systems, data management, engineering, mathematics, business technology, or a related field

Tools

Microsoft SQL Server

Oracle

Cloud databases

Data integration tools

Reporting/query tools

AWS Glue

Job description

Location: Portland, OR

Onsite Flexibility: Hybrid — Monday and Friday remote; Tuesday–Thursday onsite

Contract Details

• Position Type: Contract
• Contract Duration: 7 months
• Pay Rate: $60.00–$70.00 / Hour (USD)
• Shift / Schedule: 8 AM – 5 PM
• Work Authorization: Applicants must be authorized to work for ANY employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.

Job Summary

Performs detailed analysis of inspection and correction data across multiple source systems, databases, and applications to understand how data is structured, stored, maintained, and used by the business. Researches source databases and system tables to identify table names, field names, relationships, data types, key values, and data dependencies needed to support data conversion and migration work. Creates clear source-to-target data mappings that align legacy inspection and correction data to the new data model, schema, and ingestion requirements for a modernized database environment. Works closely with business stakeholders, application teams, database administrators, data engineers, and project teams to validate data definitions, resolve mapping questions, and ensure data meaning is preserved during conversion. Identifies data gaps, inconsistencies, duplicates, and quality issues that could impact successful ingestion into the new database, and documents recommended remediation steps. Translates business rules and operational inspection/correction processes into technical data requirements, including mapping logic, transformation rules, and validation criteria. Develops and maintains detailed documentation, including data dictionaries, table inventories, mapping workbooks, schema alignment notes, conversion assumptions, and open data issues. Supports data conversion planning, mock loads, validation activities, and issue resolution to help ensure inspection and correction data is accurately prepared for ingestion into the new database. Works independently with strong attention to detail and follows through on complex data research assignments with minimal guidance. Acts as a knowledgeable resource for project team members by explaining source-system data structures, data lineage, table relationships, and conversion impacts.

Key Responsibilities

• Perform detailed analysis of inspection and correction data across multiple source systems, databases, and applications to understand how data is structured, stored, maintained, and used by the business.
• Research source databases and system tables to identify table names, field names, relationships, data types, key values, and data dependencies needed to support data conversion and migration work.
• Create clear source-to-target data mappings that align legacy inspection and correction data to the new data model, schema, and ingestion requirements for a modernized database environment.
• Work closely with business stakeholders, application teams, database administrators, data engineers, and project teams to validate data definitions, resolve mapping questions, and ensure data meaning is preserved during conversion.
• Identify data gaps, inconsistencies, duplicates, and quality issues that could impact successful ingestion into the new database, and document recommended remediation steps.
• Translate business rules and operational inspection/correction processes into technical data requirements, including mapping logic, transformation rules, and validation criteria.
• Develop and maintain detailed documentation, including data dictionaries, table inventories, mapping workbooks, schema alignment notes, conversion assumptions, and open data issues.
• Support data conversion planning, mock loads, validation activities, and issue resolution to help ensure inspection and correction data is accurately prepared for ingestion into the new database.
• Work independently with strong attention to detail and follow through on complex data research assignments with minimal guidance.
• Act as a knowledgeable resource for project team members by explaining source-system data structures, data lineage, table relationships, and conversion impacts.

Required Skills

• Advanced attention to detail and ability to work accurately with complex data across multiple systems.
• Advanced analytical thinking skills, including the ability to investigate data issues, identify patterns, trace data lineage, and draw clear conclusions from technical research.
• Strong knowledge of relational database concepts, including tables, fields, keys, joins, data types, and schema relationships.
• Strong SQL skills for querying, profiling, validating, and reconciling data from source systems.
• Working knowledge of data modeling, schema design, data transformation, and data ingestion concepts.
• Ability to create clear and complete source-to-target mapping documentation that can be used by data engineering, development, and testing teams.
• Ability to understand business processes and translate operational rules into data requirements, mapping logic, and validation criteria.
• Strong documentation skills, including the ability to maintain data dictionaries, mapping workbooks, table inventories, issue logs, and assumptions.
• Strong collaboration skills and ability to work effectively with business users, database administrators, developers, data engineers, testers, and project stakeholders.
• Strong communication skills, including the ability to explain technical data findings in a clear, practical way for both technical and nontechnical audiences.
• Strong problem-solving skills and persistence in researching unclear, incomplete, or inconsistent data across legacy systems.
• Ability to manage competing priorities, follow through on detailed assignments, and raise risks or blockers early.

Preferred Skills

• Experience with inspection, correction, asset management, work management, field operations, or utility data.
• Experience with Microsoft SQL Server, Oracle, cloud databases, data integration tools, or reporting/query tools.
• Experience with AWS Glue, cloud databases, data integration tools, or reporting/query tools.

Required Experience

• Typically five or more years of experience working with databases, data analysis, data mapping, data conversion, schema analysis, or application data support.
• Experience analyzing relational databases and writing SQL queries to research tables, fields, joins, dependencies, and data quality issues.
• Experience creating source-to-target mapping documentation, data dictionaries, table inventories, or conversion specifications.
• Experience working across multiple business systems or legacy applications to understand data lineage, operational processes, and system-of-record decisions.

Nice-to-Have Experience

• Preferred experience with inspection, correction, asset management, work management, field operations, or utility data.
• Preferred experience with Microsoft SQL Server, Oracle, cloud databases, data integration tools, or reporting/query tools.

Education Requirements

• Bachelor's degree in computer science, information systems, data management, engineering, mathematics, business technology, or a related field, or equivalent experience.

Benefits

• Medical, Vision, and Dental Insurance Plans
• 401k Retirement Fund

About The Client

This client is a leading natural gas and electric energy company serving millions of customers across the United States. Operating across a broad geographic footprint, the organization supports critical energy infrastructure and employs professionals across engineering, data and technology, field operations, and project management disciplines who collaborate to deliver reliable energy services at scale.

About GTT

GTT is a minority-owned staffing firm and a subsidiary of Chenega Corporation, a Native American-owned company in Alaska. We highly value diverse and inclusive workplaces and support Fortune 500 organizations across banking, financial services, technology, life sciences, biotech, utilities, and retail sectors throughout the U.S. and Canada.

Job Number: 26-13854 Industry: Data & Analytics