Database Administrator

Job-ID Reference Supplier Bill Rate: *** PGE Job Title: AWS database and Data Mapping and Schema Analyst Work Hours: 8-5 Work Location: Hybrid - Mon and Fri can be remote. Tues-Thurs is onsite at WTC Can you give a high-level overview of your team size, roles, its initiatives/deliverables, and any tool/technologies specific to your team/department/project they will be supporting: The resource will support a project team focused on analyzing inspection and correction data across multiple source systems, databases, and applications. Work includes source-system research, relational database analysis, SQL querying, source-to-target data mapping, schema alignment, data dictionary/table inventory documentation, data quality issue identification, mock load support, validation, and conversion issue resolution. The role works closely with business stakeholders, application teams, DBAs, data engineers, testers, and project teams. What would you say is the top priority for the worker over the first few weeks/months?: Quickly understand source-system data structures, table relationships, business rules, and inspection/correction data lineage; begin building clear source-to-target mappings, data dictionaries, table inventories, and issue logs to support conversion planning and mock loads. Is utilities experience required? No - Preferred, but no required Top 3 Must-Haves (Hard and/or Soft Skills): 1. Strong relational database analysis skills, including tables, fields, keys, joins, dependencies, and data quality profiling 2. Experience creating source-to-target mappings, data dictionaries, table inventories, and conversion specifications 3. Advanced attention to detail, analytical thinking, and ability to document/resolve complex data lineage and mapping issues Top 3 Nice-To-Haves (Hard and/or Soft Skills) : 1. Experience with inspection, correction, asset management, work management, field operations, or utility data 2. Experience with AWS Glue, cloud databases, data integration tools, or reporting/query tools 3. Ability to translate business rules and operational processes into mapping logic, transformation rules, and validation criteria Interviews are typically done via Teams, please confirm if that is acceptable: Yes Data Mapping and Schema Analyst 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. Job Requirements: Requires a bachelor’s degree in computer science, information systems, data management, engineering, mathematics, business technology or a related field, or equivalent 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. 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. Job Competencies: 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. EEO: “Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of – Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans.”