The posting
Company Description
IntegriChain is the data and application backbone for market access departments of Life Sciences manufacturers. We deliver the data, the applications, and the business process infrastructure for patient access and therapy commercialization. More than 250 manufacturers rely on our ICyte Platform to orchestrate their commercial and government payer contracting, patient services, and distribution channels. ICyte is the first and only platform that unites the financial, operational, and commercial data sets required to support therapy access in the era of specialty and precision medicine. With ICyte, Life Sciences innovators can digitalize their market access operations, freeing up resources to focus on more data-driven decision support. With ICyte, Life Sciences innovators are digitalizing labor-intensive processes – freeing up their best talent to identify and resolve coverage and availability hurdles and to manage pricing and forecasting complexity.
We are headquartered in Philadelphia, PA (USA), with offices in: Ambler, PA (USA); Pune, India; and Medellín, Colombia. For more information, visit www.integrichain.com, or follow us on Twitter @IntegriChain and LinkedIn.
Job Description
● Work alongside AI agents as co-workers within our AI-SDLC framework — using Anthropic Claude Code, GitHub Copilot, and AWS Bedrock throughout design, development, testing, deployment, and maintenance cycles
● Drive work from Jira tickets and Confluence documentation as the source of truth for requirements, decisions, and context
● Leverage deep domain and product knowledge to evaluate and challenge requirements — ensuring they are precise, complete, and structured for effective processing by both human engineers and AI agents
● Participate actively in Agile ceremonies — sprint planning, stand-ups, retrospectives, and backlog refinement — to keep delivery on track and priorities aligned
● Surface and mitigate quality risks before they escalate — proactively communicating test coverage gaps, flagging scope concerns during planning, and helping keep the team's quality commitments on track
● Own the test strategy and automation architecture with data quality as the primary focus — spanning ETL/ELT pipeline validation, source-to-target reconciliation, functional, end-to-end (Playwright), BDD, and performance (JMeter) layers
● Build and maintain robust Python-based test frameworks and BDD feature suites — including reusable SQL and pandas/PySpark assertion libraries for data comparison, profiling, and reconciliation — that align test coverage to biopharma business requirements
● Design and govern JMeter performance test plans covering both application and data layers — pipeline throughput, load-window adherence, and large-volume query response; analyse results and drive remediation with development teams
● Own end-to-end data quality across the platform's ingestion and transformation pipelines — designing and automating validation of raw, staged, and curated layers in Snowflake and PostgreSQL
● Write and own the complex SQL that proves business logic independently of the pipeline code — reconciling source, staging, and curated layers rather than trusting transformation output at face value
● Build automated reconciliation suites covering row counts, control totals, referential integrity, deduplication, late-arriving data, slowly changing dimension handling, and idempotency on pipeline reruns
● Design and maintain reusable test data — synthetic and masked production-like datasets that exercise edge cases, nulls, boundary values, historical restatements, and malformed or out of-spec source files
● Validate orchestration behaviour end-to-end — dependency ordering, retries, partial-load recovery, backfills, incremental vs. full loads, and failure alerting
● Test schema evolution and data contracts between upstream sources and downstream consumers, catching breaking changes before they reach client-facing outputs
● Define, automate, and report on data quality rules and SLAs — completeness, accuracy, timeliness, uniqueness, and conformity — making data quality visible to the team and to stakeholders
● Serve as the go-to QA engineer for the harder test challenges — the person the team relies on when data complexity, regulatory risk, or system ambiguity is highest
● Produce clear test strategy documents, defect trend analyses, and quality reports that inform team and stakeholder decisions; communicate quality status and risk effectively to both technical and non-technical audiences
● Incorporate pharma manufacturer client needs and regulatory requirements into test coverage decisions; participate actively in incident responses and quality reviews that have direct client impact
● Apply strong analytical and problem-solving skills to trace data defects back to root cause through the pipeline — distinguishing source data issues from transformation logic defects and orchestration failures — anticipating failure modes and designing coverage for them proactively rather than reactively; evaluate quality trade-offs and drive decisions with appropriate rigour
● Demonstrate full accountability for your own work and the team's quality output — holding yourself answerable to team-level quality outcomes, not just individual test deliverables; proactively managing risks, communicating progress, and owning quality end-to-end
● Lift the overall quality output of the team — through proactive test design collaboration, knowledge sharing, unblocking, and consistently raising the bar on what the team ships
● Stay current with the team's evolving test toolset — including AI-augmented testing practices, Playwright updates, BDD patterns, and biopharma regulatory developments — and actively bring relevant updates into team practices
● Partner effectively across backend developers, UI/UX developers, product analysts, and domain stakeholders — communicating clearly within a geographically distributed team
● Mentor junior QA engineers and champion quality best practices across the team
● Evaluate and integrate AI-powered testing tools into the QA workflow
Qualifications
● 7+ years in software quality engineering, with the majority of that time spent on data-centric testing — ETL/ELT pipelines, data warehouses, and reporting/consumption layers. Strong expertise in requirement analysis, test data design, test planning, and detailed test case design across automation and manual testing.
● Any experience with AWS/Cloud hosted applications is an added advantage.
● Expert-level SQL (MUST) — able to independently write and tune complex queries against Snowflake, PostgreSQL and MySQL (multi-table joins over large fact/dimension tables, window functions, CTEs, aggregations, set operations) to validate transformation logic without depending on developers
● 4+ years specifically testing data pipelines / ETL-ELT processes end-to-end — source-to-target mapping validation, reconciliation, data quality rule design, and root-cause analysis of data defects
● Hands-on experience with a cloud data warehouse (Snowflake strongly preferred) — comfortable with stages, streams, tasks, time travel, clustering, and reading query profiles for tuning
● Working knowledge of pipeline orchestration and transformation tooling (Airflow, dbt, AWS Glue, Step Functions, or equivalent) and of common ingestion formats (CSV, fixed-width, JSON, Parquet; EDI/X12 an advantage)
● Python data-handling skills applied to testing — pandas, PySpark, or equivalent — for building comparison, profiling, and reconciliation utilities at scale
● Exposure to data quality frameworks such as Great Expectations, dbt tests, or Soda, or experience building equivalent in-house capability
● 3+ years of test automation across UI and API layers — creating, executing, and maintaining automated tests with Selenium WebDriver (v3+)/Playwright, with programming experience in Python (MUST) — complementing, not replacing, the core data testing focus
● Deep BDD expertise — framework design, Gherkin authoring, step library architecture, living documentation
● Proven JMeter experience — test plan design, distributed execution, and results analysis
● Hands-on experience working in an AI-augmented or agentic development/testing environment (e.g. Claude Code, Copilot, AWS Bedrock, or equivalent)
● Experienced working with Agile methodologies, such as Scrum, Kanban
● Strong analytical and problem-solving skills with a track record of owning data quality outcomes end-to-end — accountable to team-level quality outcomes, not just individual deliverables
● Influences technical decisions on the team through well-supported proposals and demonstrated expertise; beginning to shape team practices through example and mentorship
● Excellent written and verbal communication skills within a geographically distributed, cross functional team
● Key competencies required: Problem-Solving, Analytical, Collaboration, and Accountability. Strong communication skills & stakeholder management. Advantage if,
● Has Healthcare/Life Sciences domain experience — particularly pharma commercial data (distributor 867/852 files, chargebacks, claims, gross-to-net, or master data management)
● Has experience designing and enhancing test automation frameworks, especially data validation frameworks built in-house
● Team leading experience Professional Approach
● Ready to work in flexible working hours and collaborate with US/India/Colombia teams
● Good communication skills (written, verbal, listening, and articulation)
Additional Information
What does IntegriChain have to offer?
- Mission driven: Work with the purpose of helping to improve patients' lives!
- Excellent and affordable medical benefits + non-medical perks including Flexible Paid Time Off and much more!
- Robust Learning & Development opportunities including over 700+ development courses free to all employees
#LI-NS1
IntegriChain is committed to equal treatment and opportunity in all aspects of recruitment, selection, and employment without regard to race, color, religion, national origin, ethnicity, age, sex, marital status, physical or mental disability, gender identity, sexual orientation, veteran or military status, or any other category protected under the law. IntegriChain is an equal opportunity employer; committed to creating a community of inclusion, and an environment free from discrimination, harassment, and retaliation.
