Data Quality

Data Quality Jobs

79 jobs found

17d ago

Sr Data Engineer

BECU Washington, WA

Washington, WA

17d ago

$142k - $205k/yr Full time Senior Azure Cloud

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Job Description

Build and support enterprise-class data pipelines and scalable cloud data solutions in a hybrid role in Washington state.

Responsibilities

Design and develop complex multi-tier systems covering analysis, coding, testing, debugging, and documentation for cloud-native data solutions and integration services
Coordinate, support, and execute design and development of complex data workflows, including batch, near real-time, and API-based integrations
Design and support prototypes, proofs of concept, and scalable data solutions that align technical delivery with business needs
Support metadata management, master data policies, data quality standards, lineage, and governance practices within data workflows and pipelines
Organize and guide data curation policies across data platforms and workflows based on technical requirements
Support, mentor, and coordinate small to medium-sized teams through design reviews, code reviews, testing, and development activities
Partner with Architects, Product Owners, and leadership teams to document technology roadmaps, cloud modernization initiatives, and future-state data platform strategies
Contribute to coding standards, CI/CD practices, automated testing, and code quality initiatives while shaping and improving engineering best practices
Support monitoring and observability capabilities to improve pipeline performance, reliability, and operational outcomes
Use automation and AI-assisted development tools, including GitHub Copilot and related technologies, to improve productivity and code quality
Collaborate with architecture, governance, security, and platform engineering teams to deliver secure, scalable, reusable data products and services
Present technical topics to engineering audiences and contribute to growing data engineering capabilities across the organization
Perform responsibilities in line with BECU Competencies, compliance, regulatory, and Information Protection requirements

Requirements

Bachelor’s degree in computer science or related discipline, or equivalent work experience
Minimum 5 years of functional experience in data engineering
Minimum 4 years coding experience with Python, Scala, Java, and SQL
Demonstrated experience with cloud technologies including Azure, AWS, and GCP
Demonstrated experience with modern data platforms including Azure Synapse, Azure Databricks, Redshift, Big Query, and Snowflake
Demonstrated experience with ETL/ELT, SQL, and cloud data integration tools, including Azure Data Factory, Azure SQL, Cosmos DB, Event Hubs, Azure Storage, Azure functions, Container apps, and API Management
Demonstrated experience with SQL, data modeling, data warehousing, data analysis, and supporting enterprise-scale operational data stores (ODS), data warehouses, and data lake or Lakehouse solutions
Experience with CI/CD systems and tools such as Azure DevOps and GitHub
Experience with Git, including code reviews, pull requests, and branching standards such as Git Flow or Trunk-Based Development
Knowledge of financial services concepts, regulations, and data domains including banking, lending, deposits, payments, and risk management
Experience building AI-ready data products and supporting AI agent architectures
Experience with GitHub Copilot or AI-assisted Azure OpenAI, Azure AI Search, Copilot Studio, AI Foundry, MCP integrations, or related AI technologies
Previous experience with master data (MDM), metadata, data quality, data lineage, data cataloging, and data governance tools including Alation, Erwin, Collibra, Azure Purview, Infosphere, and Informatica MDM
Experience with Test Driven Development concepts, methods, and tools, including unit testing, integration testing, or performance/load testing
Proven ability to deliver highly scalable data solutions across the data lifecycle from ideation to retirement
Proven ability to stay current on emerging technologies and new applications of existing data technologies through work or continuing industry or education involvement
Proven experience leading and collaborating across teams and business units to deliver solutions through the SDLC
Experience presenting to technically adept audiences

Technologies

Python, Scala, Java, SQL
Azure, AWS, GCP
Azure Synapse, Azure Databricks, Redshift, Big Query, Snowflake
Azure Data Factory, Azure SQL, Cosmos DB, Event Hubs, Azure Storage, Azure functions, Container apps, API Management
Azure DevOps, GitHub, Git
Git Flow, Trunk-Based Development
GitHub Copilot, Azure OpenAI, Azure AI Search, Copilot Studio, AI Foundry, MCP
Alation, Erwin, Collibra, Azure Purview, Infosphere, Informatica MDM
ETL, ELT, CI/CD

Benefits

401(k) Company Match (up to 3%)
4% annual contribution to your 401(k) by BECU
Medical, Dental and Vision (family contributions as well)
PTO Program + Exchange Program
Tuition Reimbursement Program
BECU Cares volunteer time off + donation match

Pay Range

Target Pay Range: $141,800.00 - $173,300.00 annually
Full Pay Range: $110,100.00 - $204,900.00 annually
Additional compensation incentives may be available for the hired applicant
Incentives are performance based and targets vary by role

Residency / Location Requirements

Candidates must be residents of WA, OR, ID, AZ, TX, GA, SC, NC, CA, or VA
If located in Washington state and within a reasonable driving distance from Tukwila, come into HQ on Tuesdays & Wednesdays
For candidates outside the commute distance of TFC in approved remote work locations, this role is remote
Remote or onsite, engagement and inclusion in a collaborative environment are emphasized

What You’ll Gain

Influence the design and evolution of modern cloud-based data platforms at enterprise scale
Exposure to cutting-edge technologies across cloud, data engineering, automation, governance, and AI-enabled solutions
Opportunities to mentor and develop other engineers while contributing to technical excellence and continuous improvement
Collaboration with cross-functional teams to deliver secure, scalable, reusable data products that support business outcomes
Build solutions that support analytics, operational decision-making, and future AI-driven capabilities

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17d ago

Site Reliability Data Engineer

Leidos San Diego, CA

San Diego, CA

17d ago

$87k - $157k/yr Full time Ansible Business Intelligence Cloud Infrastructure

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Job Description

Leidos is seeking a Site Reliability Data Engineer to support the SMIT program for the Navy. The role focuses on building and operating secure enterprise data solutions and automated testing frameworks that validate resilience, performance, and failure scenarios across hybrid cloud and on-prem environments, while meeting service level objectives (SLOs).

Responsibilities

Design, develop, test, deploy, and maintain scalable ETL/ELT pipelines that collect, transform, validate, and deliver structured and unstructured data from enterprise systems, applications, APIs, logs, files, and databases.
Build and optimize data models, schemas, tables, views, and curated datasets to support analytics, business intelligence, operational reporting, and downstream application requirements.
Develop data-processing solutions using SQL, Python, and other approved technologies, applying reusable engineering patterns, source control, peer review, and documented release practices.
Integrate cloud and on-premises data platforms while supporting secure data movement, interoperability, availability, retention, and performance across hybrid enterprise environments.
Implement automated data-quality checks, reconciliation controls, monitoring, alerting, and exception handling to detect incomplete, inaccurate, duplicated, delayed, or failed data flows.
Troubleshoot pipeline failures, data discrepancies, performance degradation, access issues, and integration defects, performing root-cause analysis and implementing corrective and preventive actions.
Coordinate with analysts, business intelligence developers, data owners, system administrators, and mission stakeholders to define data requirements, source-to-target mappings, transformation rules, service expectations, and acceptance criteria.
Apply data governance, security, privacy, least-privilege access, auditability, and records-retention requirements across the data lifecycle in coordination with cybersecurity and compliance teams.
Support platform upgrades, data migrations, modernization initiatives, capacity planning, and performance tuning while minimizing disruption to production services.
Create and maintain technical documentation, including architecture diagrams, data dictionaries, lineage documentation, interface specifications, runbooks, standard operating procedures, and troubleshooting guides.
Participate in Agile planning, backlog refinement, technical reviews, demonstrations, incident response, and after-hours support activities when required to sustain mission-critical services.
Develop and execute tests focused on system resilience, performance underload, and failure scenarios.
Work with other Site Reliability Engineers and development teams to create automated testing frameworks that simulate real-world conditions and validate system behavior under normal and stress conditions, ensuring services are resilient and meet established SLOs.
Support the operations and maintenance of the enterprise network.

Requirements

B.S Degree and 4–8 years of prior relevant experience, or Masters with 2–6 years of prior relevant experience in data engineering, computer science, information systems, software engineering, mathematics, or a related technical discipline, with at least four years of relevant experience. Additional directly related experience may be considered in place of a degree.
U.S. citizen with an active DoD Secret Security Clearance.
Ability to possess and maintain an IAT Level II certification that satisfies applicable DoD cybersecurity workforce requirements.
Location requirement: located in (or able to work onsite at Navy Base as required) either San Diego, California, the Hampton Roads, Virginia area, or Jacksonville, FL.
At least three years of hands-on experience developing, operating, or supporting production data pipelines, data integrations, data warehouses, data lakes, or comparable enterprise data solutions.
Demonstrated proficiency with SQL and at least one general-purpose scripting or programming language, such as Python, for data extraction, transformation, validation, automation, and troubleshooting.
Experience with ETL/ELT, relational data structures, data modeling, schema design, source-to-target mapping, data quality, metadata, and lifecycle management.
Experience integrating data from multiple source types including relational databases, APIs, flat files, application data, system logs, or message-based interfaces.
Working knowledge of cloud and on-premises infrastructure concepts related to authentication and authorization, network connectivity, encryption, secure file transfer, and service accounts as they relate to data engineering.
Experience diagnosing production data issues, analyzing logs and metrics, resolving failed jobs or performance problems, and documenting root cause and corrective action.
Ability to work independently and collaboratively in a high-tempo operational environment, manage competing priorities, communicate technical information clearly, and produce complete technical documentation.
Working knowledge of PowerShell, Python, and Ansible, with practical familiarity using large language models (LLMs) and AI-enabled tools.

Technologies

SQL
Python
PowerShell
Ansible
LLMs, AI-enabled tools
ETL, ELT
Agile/DevOps

Benefits

Competitive compensation
Health and Wellness programs
Income Protection
Paid Leave
Retirement

Nice to Have

Business intelligence experience, including development or support of dashboards, reports, semantic models, key performance indicators, and self-service analytics solutions; experience with Microsoft Power BI (and associated DAX knowledge) is highly desirable.
Microsoft Certified: Azure Administrator Associate (AZ-104) certification.
Hands-on experience with Azure data and analytics services such as Azure Data Factory, Azure SQL, Azure Storage, Synapse Analytics, Databricks, or comparable cloud data platforms.
Familiarity with Security Technical Implementation Guides (STIGs), the Risk Management Framework (RMF), vulnerability management processes, system hardening, security controls, and applicable compliance frameworks.
Experience using automation, configuration-management, source-control, or continuous integration and delivery tools such as Ansible, Jenkins, and Bitbucket.
Experience designing or supporting data solutions in classified, DoD, federal government, or other highly regulated environments.
Experience with modern data-platform concepts including data lakes, lake houses, dimensional modeling, streaming or event-driven data, distributed processing, or containerized workloads.
Experience implementing data cataloging, lineage, master or reference data, role-based access controls, audit logging, backup and recovery, and disaster-recovery practices.
Relevant technical certifications in Azure, data engineering, database administration, analytics, cloud architecture, or security.
Strong customer engagement, requirements analysis, technical presentation, mentoring, and cross-functional collaboration skills.
Experience with graph databases (e.g., Neo4j) and query languages such as Cypher, including modeling entities and relationships as a property graph.
Familiarity with knowledge graphs, ontologies, or semantic data models and controlled vocabularies.
Experience with entity resolution / record linkage and reconciling conflicting values across multiple authoritative sources into a single trusted record.

Location and Salary

Location: San Diego, CA (onsite)
Salary: USD 87,100 - 157,450 per year
Minimum Experience: 3 years

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23d ago

Lead Data Engineer

Deloitte McLean, VA

McLean, VA

23d ago

$111k - $175k/yr Full time Manager Big Data Data

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Job Description

Deloitte’s AI & Data team is seeking a Lead Data Engineer to help shape how enterprise data is structured, governed, and delivered. In this onsite role in McLean, VA, you will provide technical leadership across enterprise data architecture, canonical data modeling, platform standards, and migration planning. You will also collaborate closely with data scientists, analysts, and business stakeholders to ensure architecture decisions align with operational needs and future analytical goals.

What you will do

Define and govern enterprise data architecture, including logical and physical data models, database schemas, and hierarchical and recursive data structures.
Design and oversee canonical data models, ontology structures, and platform data standards that support consistency, scalability, and system performance.
Provide technical oversight for data engineering delivery, including pipeline design, schema changes, code reviews, quality controls, and architectural approvals.
Direct data migration planning and execution, including sequencing, mapping, validation, reconciliation, rollback planning, and issue resolution during cutover.
Partner with data scientists, analysts, and business stakeholders to align architecture decisions with current operational requirements and future analytical needs.

Required qualifications

Bachelor’s degree
5+ years designing database architectures, including recursive and hierarchical data structures
4+ years with SQL and data modeling across relational, dimensional, and graph-oriented models
4+ years with PySpark and ETL/ELT pipeline tooling (extract, transform, load and extract, load, transform)
Ability to obtain and maintain the required clearance for this role
Ability to travel 25%, on average
Must be legally authorized to work in the United States without employer sponsorship, now or in the future

Technologies you will work with

SQL
PySpark
ETL (extract, transform, load)
ELT (extract, load, transform)

How you will succeed

Work independently while collaborating effectively as part of a team
Use strong written and verbal communication
Maintain meticulous attention to detail and quality of work product
Build and sustain professional relationships
Lead projects or workstreams, managing and prioritizing multiple tasks in a fast-paced environment
Mentor others by providing clear guidance and support

Preferred experience

Experience leading enterprise data migration efforts from legacy systems to target-state platforms
Experience leading data engineering teams or technical workstreams
Experience translating business requirements into technical data architecture designs

Compensation: USD 110,700 to 174,600 per year.

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26d ago

SQL Data Analyst

Beacon Hill Staffing Group Charlotte, NC

Charlotte, NC

26d ago

Full time Business Analytics Data Data Analysis

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Job Description

Support a Data Quality and Data Lineage team by investigating data issues, analyzing datasets with SQL, and helping align business and technical stakeholders in a large enterprise environment.

Responsibilities

Investigate data issues and identify root causes
Perform SQL analysis to examine data behavior and support troubleshooting
Validate data quality as part of ongoing data checks
Research data lineage to understand where data originates and how it changes
Serve as a bridge between business and technical teams to align understanding and next steps

Requirements

5+ years of SQL experience, including ad hoc queries, data validation, and data quality work
5+ years in a large enterprise environment
Strong analytical, troubleshooting, and problem-solving skills
Experience translating technical concepts for business users
Knowledge of AI tools to improve efficiency

Location

Charlotte, NC (onsite)

Benefits

Medical, dental, vision
Federal and state leave programs as required by applicable agency regulations for eligible candidates

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29d ago

Data Analyst

Network Rail Consulting Seattle, WA

Seattle, WA

29d ago

Full time Data Analysis Data Analytics Data Governance

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Job Description

Network Rail Consulting is hiring a Data Analyst for our Seattle team, supporting internal project teams and clients across the US. You will extract, compile, analyze, and visualize data to help drive clear insights and practical next steps. This hybrid role offers flexible working practices, a benefits package designed to support your health and long-term planning, and the opportunity to work on real client dashboards and reporting.

What you’ll do

Compile data from client systems, including Trapeze EAM, Maximo EAM, and various LMS / EAM / ERP systems for training and inventory data.
Perform data mapping to support data migration and data conformance evaluation.
Develop data definition/dictionaries with SMEs and establish data standards in partnership with a data governance program.
Evaluate data quality against agency data quality metrics.
Develop reference data and taxonomies to support consistent reporting and analysis.
Extract, organize, and analyze data for trending and comparison of ERP/EAM Program needs and requirements.
Design and build dashboards in Excel and Power BI for internal and external use.
Prepare PowerPoint presentations for internal and external stakeholders.
Communicate remediation plans needed and develop plans to support next-step work on data remediation; provide feedback on remediation recommendations.
Ensure data quality and compliance with applicable state and federal laws and regulations.
Assist the Client, Project Manager, or project team as required.

What you bring

Recent graduate status, with a bachelor’s or master’s Degree (or equivalent) in a relevant field.
Highly skilled in Power BI, Excel, and PowerPoint.
Experience with MS Co-Pilot.
Strong analytical and critical thinking skills, with proficiency in spreadsheet manipulation and attention to detail.
Excellent communication and writing, including formal report, presentation, and note writing skills.
Ability to be a visual storyteller that makes data easy to understand.
Capability to work independently with clients as an excellent listener.
EAM / CMMS applications experience is strongly preferred.
ERP / LMS / GIS applications experience is desirable but not essential.

Technology you’ll use

Trapeze EAM, Maximo EAM, LMS, EAM, ERP, Excel, Power BI, PowerPoint, MS Co-Pilot, and EAM / CMMS applications. Experience with ERP / LMS / GIS applications is also considered desirable.

Benefits and working model

Competitive compensation packages
Healthcare insurance premiums (100% paid for by us)
Generous vacation leave entitlement
401K with employer matching contributions
Access to Employee Discount Program via LifeMart
Flexible working practices, including hybrid (home/office) working and flexible working hours

About the role

Network Rail Consulting supports multiple US clients from strategic locations in Washington DC, New York City, and Boston, as well as West Coast clients from offices in California and Seattle. Initial client work will be with Sound Transit and King County Metro staff, focused on data related to work orders, inventory, training data, and project dashboards.

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29d ago

Data Analyst

AssistRx, LLC Miami, FL

Miami, FL

29d ago

$80k - $100k/yr Full time Marketing Analytics Application Support

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Job Description

The Data Analyst at AssistRx, LLC leads onboarding of data assets into a cloud data platform, monitors data quality, and coordinates with stakeholders to address issues as they arise. This onsite role in Florida supports data mapping, compliance-oriented file review, mapping tool configuration, and ongoing updates to data specifications.

Location

Florida (onsite)

Compensation

USD 79,948 - 99,960 per yearly

Role Overview

This position is responsible for leading the onboarding of data assets into the cloud data platform. The Data Analyst also monitors data for quality issues and communicates with stakeholders regarding resolution activities.

Key Responsibilities

Work with partners to assist in creating a data mapping aligned to defined specifications.
Communicate directly with leadership about data needs and key deadlines.
Research, identify, and address data quality issues reported through onboarding or discovered during new file submission, collaborating with clients and the team on resolution.
Field incoming requests and questions related to data specifications.
Review received files for compliance with data needs, including testing files and identifying business rules to be configured in the mapping tool.
Configure the mapping tool to translate source data into the desired format, including tool testing.
Provide clear documentation to internal resources and customers.
Serve as the resident expert for data requirements and specifications.
Stay current on ongoing changes and evolution of data specifications.
Lead co-worker trainings focused on data specifications and requirements.
Perform other related duties as assigned by management.

Required Qualifications

Bachelor’s Degree (BA) from a four-year college or university, or 8+ years of related experience and/or training, or an equivalent combination of education and experience.
Computer skills.
Experience with ETL, analytic-based data-driven reporting, Tableau, and SQL.
Experience with Server, Salesforce, and Snowflake.
Experience with healthcare and/or pharmacy data is preferred.
Previous client-facing experience.
Must be extremely responsive and able to work under pressure in crisis with a strong sense of urgency.

Technology Stack

ETL
Tableau
SQL
Salesforce
Snowflake
Server

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1mo ago

Junior Data Analyst

Morgan Stanley Dallas, TX

Dallas, TX

1mo ago Closed

$80k - $100k/yr Full time Python Data Analysis Data Analytics

This position is no longer accepting applications (closed Sep 16, 2026).

Job Description

Join Morgan Stanley’s NFR Data & Analytics team in Dallas, TX (onsite) and help power investigative analytics tied to Financial Crime Risk and Crypto. This Junior Data Analyst role supports data wrangling, reconciliation, and reporting workflows, with a focus on accuracy, data quality, and audit-ready documentation. The position’s work location is temporary and will transition to 1445 Ross Ave.

Compensation: expected base pay rates are between $80,000 and $100,000 per year at the commencement of employment. Actual base pay will be determined on an individualized basis and is only part of the total compensation package. Depending on the position, the package may include commission earnings, incentive compensation, discretionary bonuses, other short- and long-term incentive packages, and other Morgan Stanley sponsored benefit programs.

On-site process: in-person interviews will be required for the role.

What you’ll do

Perform foundational data wrangling and preparation across datasets related to Fraud, GFC, and blockchain transactions.
Assist with data reconciliation and validation to maintain accuracy and completeness of investigation datasets.
Support reporting outputs and recurring analytical deliverables, including ongoing production reporting support and recurring data refreshes.
Partner with senior analysts to structure and clean data for downstream investigative workflows.
Run data quality checks, identify basic issues or anomalies, and escalate inconsistencies as appropriate.
Collaborate with stakeholders across Fraud, GFC, and Technology teams to support cross-functional data needs.
Handle restricted datasets accessible only to US-based staff while following data governance and access controls.
Document data processes, assumptions, and transformations in a clear, audit-ready format.

What you bring

0-3+ years of experience in data analysis, data wrangling, or related analytical roles.
Working knowledge of SQL or similar query languages; exposure to data tools such as Python, Alteryx, and Excel is a plus.
Basic understanding of data validation, reconciliation, and data quality practices.
Strong attention to detail, especially in data accuracy and control-oriented environments.
Ability to work with structured and semi-structured datasets in a regulated setting.
Interest in Financial Crime and Crypto-related analytics.
Strong communication skills to follow requirements and translate data into structured outputs.
Ability to manage multiple tasks in a team-oriented, deadline-driven environment.
Willingness to learn new tools, datasets, and analytical approaches in a rapidly evolving domain.