Data Architect / Quality Assurance Engineer

City of Philadelphia•Philadelphia, PA

10d•Hybrid

About The Position

The Data Architect / Quality Assurance Engineer will help define, document, and improve the data models, standards, validation frameworks, and quality assurance practices that support the City’s enterprise data integration ecosystem. This position will work across departments, programs, systems, and technical teams to understand business processes, source-system behavior, data definitions, data quality issues, and integration needs. The role will help translate that understanding into enterprise data models, data contracts, validation rules, metadata, quality checks, and architectural guardrails that make City data more consistent, trustworthy, reusable, and scalable. The Data Architect / Quality Assurance Engineer will play a key role in reducing downstream errors, improving API and integration design, supporting data governance, and ensuring that enterprise data products are designed with quality and reuse in mind from the beginning. The position will support priority departmental and enterprise modernization efforts, while also contributing to broader enterprise data architecture and data quality work across CityGeo’s portfolio. We are looking for a candidate who can bridge business process analysis, data architecture, quality assurance, and practical implementation. This role is well suited for someone who enjoys working with stakeholders to understand how data is produced and used, while also creating the standards, models, and validation practices that make data more reliable across the enterprise. Some prominent services the team is responsible for include DataBridge, OIT’s enterprise data warehouse, AIS, the City’s custom address information systems which supports public address search and internal geocoding, and Databridge-Airflow, a custom workflow generator and orchestrator for departmental integrations (https://metadata.phila.gov/) and open data publishing. Some examples of OIT’s commitment to serving the public through the effective and innovative integration of City open data include: https://Atlas.phila.gov https://property.phila.gov https://Openmaps.phila.gov https://streetsmartphl.phila.gov/ www.phila.gov/solarmap www.phila.gov/stressmap

Requirements

Bachelor’s degree or advanced degree in Computer Science, Information Systems, Data Science, Data Analytics, GIS, Public Policy, Engineering, or a related field. Equivalent work experience may be considered.
Five or more years of progressively responsible experience in data architecture, data engineering, data quality assurance, data governance, business intelligence, systems analysis, database design, or a related role.
Demonstrated experience designing data models, documenting data definitions, analyzing source systems, or creating validation frameworks.
Proven experience working with SQL and relational databases.
Experience working with technical teams and business stakeholders to define requirements, data rules, data models, or quality standards.
Experience supporting enterprise integrations, APIs, data warehouses, reporting systems, analytics platforms, or operational data products.
Dedication to making Philadelphia municipal government more robust, efficient, equitable, and data-informed.
Strong knowledge of data modeling, database design, schema design, normalization, dimensional modeling, or related data architecture practices.
Strong SQL skills and experience working with relational databases, preferably Postgres and PostGIS.
Experience defining data quality rules, validation checks, test cases, acceptance criteria, and QA workflows.
Familiarity with data governance, metadata management, data lineage, data dictionaries, data inventories, master data management, and reference data.
Familiarity with API design, data contracts, JSON schemas, OpenAPI specifications, or similar approaches to defining data exchange standards.
Ability to create diagrams, documentation, data dictionaries, entity relationship models, process maps, and quality reports.
Clear and concise written and verbal communication.
Strong facilitation and stakeholder engagement skills.
Strong analytical thinking and attention to detail.
Ability to understand business processes and translate them into data models, rules, and technical requirements.
Ability to work across multiple domains, departments, systems, and stakeholder groups.
Ability to balance governance, quality, delivery, and operational practicality.
Ability to identify patterns, inconsistencies, risks, and opportunities for standardization.
Commitment to documentation, transparency, public service, and continuous improvement.

Nice To Haves

Experience working with Python, DBT, SQL-based testing, automated QA frameworks, or data validation tools is preferred.
Familiarity with ETL/ELT pipelines, data warehouses, data lakes, integration platforms, and workflow orchestration tools such as Airflow.
Experience with Git/GitHub, CI/CD practices, and modern data engineering workflows
Experience working with spatial datasets, addressing data, permitting, property, service request, inspection, or other municipal datasets is a plus.
Experience working in a public-sector, civic technology, or large enterprise environment is a plus.
Previous work in a public-sector or large-organization setting is a plus.

Responsibilities

Lead data discovery and requirements-gathering sessions with departments, programs, vendors, and technical teams to understand business processes, source systems, data flows, data definitions, and data quality concerns.
Design conceptual, logical, and physical data models that support enterprise integrations, APIs, reporting, analytics, open data, and operational systems.
Define reusable data architecture patterns, naming conventions, entity relationships, identifiers, reference data standards, and master data concepts.
Develop data contracts, schema standards, field definitions, validation rules, and acceptance criteria for new and existing integrations.
Establish systematic data quality checks for completeness, accuracy, consistency, validity, uniqueness, timeliness, referential integrity, and business-rule compliance.
Work with data engineers to implement automated validation and quality assurance workflows using SQL, Python, DBT tests, metadata tools, or similar approaches.
Review integration designs, pipeline logic, API structures, and data models to ensure they align with enterprise standards and long-term reuse needs.
Identify and document data quality issues, root causes, source-system constraints, transformation risks, and downstream impacts.
Develop quality assurance processes for integration releases, schema changes, source-system changes, API changes, and data product updates.
Support metadata management, data lineage, data dictionaries, data inventories, and governance documentation for enterprise data assets.
Partner with data stewards and department stakeholders to clarify definitions, ownership, update frequency, quality expectations, and appropriate use of data.
Partner with security, privacy, legal, and program teams to ensure sensitive or restricted data is handled according to appropriate rules and expectations.
Contribute to enterprise data governance, data sharing, API development, open data, and integration standards.
Produce clear documentation, diagrams, validation reports, data quality scorecards, and technical guidance for both technical and non-technical audiences.
Help establish a culture of quality, reuse, and accountability across City data integration work.