Qode
Financial Services
QALead-Data&PipelineQuality
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“QA Lead - Data & Pipeline Quality at Qode. Skills: Data Quality, Pipeline Quality, Wealth Management Data, AI-Augmented QA. Own and evolve QA strategy for data pipelines. Own and evolve QA strategy for ETL/ELT workflows”
Industry & Context.
Root cause analysis; Anomaly detection; Data quality failures; Data quality problems
What They're Looking For.
Must Have
5–8 years of experience in data quality, QA engineering, or data testing, Direct exposure to wealth management data domains, Hands-on experience validating wealth management datasets, Experience designing and executing reconciliation QA processes, Proficiency with SQL, Experience with at least one scripting language, Experience working within Microsoft Azure cloud environments, Understanding of ETL/ELT pipeline architecture, Demonstrated use of AI tools in day-to-day QA work
Nice to Have
Experience with Databricks or PySpark, Familiarity with Delta Lake, Unity Catalog, or data lakehouse quality frameworks, Exposure to custodial data feeds and formats, Experience with advisor technology platforms, Knowledge of financial instruments, Familiarity with data observability tools, Experience in a fintech, WealthTech, RIA, or asset management environment
What You'll Do.
Own and evolve QA strategy for data pipelines
Own and evolve QA strategy for ETL/ELT workflows
Own and evolve QA strategy for financial data
Design and implement scalable test frameworks
Define QA standards for data engineering team
Define QA best practices for data engineering team
Define documentation requirements for data engineering team
Lead test planning for pipeline builds
Lead test planning for platform changes
Lead test case design for pipeline builds
Lead test case design for platform changes
Lead test execution for pipeline builds
Lead test execution for platform changes
Validate accuracy of wealth management datasets
Validate completeness of wealth management datasets
Design reconciliation QA processes
Run reconciliation QA processes
Build automated data quality checks
Build threshold alerts
Build validation rules
Investigate root causes of data quality failures
Document root causes of data quality failures
Partner with engineering to drive permanent fixes
Lead QA efforts across data ingestion layers
Lead QA efforts across data transformation layers
Lead QA efforts across data delivery layers
Design regression test suites
Collaborate with data engineers during development
Embed QA checkpoints earlier in build cycle
Validate data outputs against business requirements
Validate data outputs against financial data specifications
Leverage AI tools to accelerate test case generation
Leverage AI tools to accelerate anomaly detection
Leverage AI tools to accelerate QA documentation
Identify opportunities to apply AI/ML techniques
Apply AI/ML techniques to data quality problems
Apply AI/ML techniques to automated break detection
Apply AI/ML techniques to outlier identification
Apply AI/ML techniques to pattern-based validation
Champion AI-forward approach to QA
Bring practical recommendations for tooling improvements
Partner with data engineering to align on data
Partner with operations to align on data quality
Partner with service teams to align on data
Partner with data engineering to align on resolution
Partner with operations to align on resolution workflows
Partner with service teams to align on resolution
Serve as QA voice in sprint planning
Serve as QA voice in pipeline design reviews
Serve as QA voice in platform release cycles
Mentor junior QA team members
Help build quality-first culture across data organization
How You'll Work.
Team & Collaboration
Data engineering teams; Operations teams; Service teams; Cross-functional teams; Agile teams
Communication Scope
Documentation skills
Process & Methodology
Sprint planning, Release cycles
Full Job Description
QA Lead — Data & Pipeline Quality Employment Type: Full-Time Location: Austin, TX About Incedo Incedo Inc. is a high-growth Digital, Data and AI Transformation Specialist firm headquartered in New Jersey. We are a long-term strategy execution partner for Fortune 500 enterprises, operating at the intersection of business and technology across Banking & Payments, Wealth Management, Telecom, Hi-Tech, and Life Sciences. We are building Incedo 4.0 - an AI-native, execution-focused, founder-led organization designed for scale, speed, and long-term impact. Incedo delivers ROI from AI @ Scale through the “Power of 3”: * Deep domain expertise * AI & Data capabilities * Engineering & Operations excellence About the Role We are seeking an experienced QA Lead to own data and pipeline quality across our wealth management technology platform. This is a critical role responsible for ensuring the integrity, accuracy, and reliability of the financial data that advisors, clients, and operations teams depend on every day. The ideal candidate has a strong wealth management background and understands what's at stake when data is wrong — whether that's a position break, a misallocated transaction, or a stale security price. You will design and lead QA frameworks, own test strategy for data pipelines, and serve as the last line of defense before bad data reaches downstream consumers. You are also expected to actively leverage AI tooling to improve coverage, speed, and the quality of your team's output. Key Responsibilities QA Strategy & Test Framework * Own and evolve the end-to-end QA strategy for data pipelines, ETL/ELT workflows, and financial data integrations * Design and implement scalable test frameworks covering data validation, schema integrity, transformation accuracy, and business rule compliance * Define QA standards, best practices, and documentation requirements for the data engineering team * Lead test planning, test case design, and execution across new pipeline builds and
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