About the role

We are seeking an accomplished Data Engineer to join our dynamic and rapidly expanding Tech Ops division. With significant projected growth, this is an opportunity to drive meaningful technical impact. In this role, you will work directly with customers, data vendors, and internal engineering teams to design, implement, and optimize complex data integration solutions within a modern, large‑scale cloud environment.

You will leverage advanced skills in distributed computing, data architecture, and cloud-native engineering to enable scalable, resilient, and high‑performance data ingestion and transformation pipelines. As a trusted technical advisor, you will guide customers in adopting Abacus’s core data management platform and ensure high-quality, compliant data operations across the lifecycle.

Your day to day

• Architect, design, and implement high-volume batch and real-time data pipelines using PySpark, SparkSQL, Databricks Workflows, and distributed processing frameworks.
• Build end‑to‑end ingestion frameworks integrating with Databricks, Snowflake, AWS services (S3, SQS, Lambda), and vendor data APIs, ensuring data quality, lineage, and schema evolution.
• Develop data modeling frameworks, including star/snowflake schemas and optimization techniques for analytical workloads on cloud data warehouses.
• Lead technical solution design for health plan clients, creating highly available, fault-tolerant architectures across multi-account AWS environments.
• Translate complex business requirements into detailed technical specifications, engineering artifacts, and reusable components.
• Implement security automation, including RBAC, encryption at rest/in transit, PHI handling, tokenization, auditing, and compliance with HIPAA and SOC 2 frameworks.
• Establish and enforce data engineering best practices, such as CI/CD for data pipelines, code versioning, automated testing, orchestration, logging, and observability patterns.
• Conduct performance profiling and optimize compute costs, cluster configurations, partitions, indexing, and caching strategies across Databricks and Snowflake environments.
• Produce high-quality technical documentation including runbooks, architecture diagrams, and operational standards.
• Mentor junior engineers through technical reviews, coaching, and training sessions for both internal teams and clients.

What you bring to the team

• Bachelor’s degree in Computer Science, Computer Engineering, or a closely related technical field.
• 7+ years of hands‑on experience as a Data Engineer working with large‑scale, distributed data processing systems in modern cloud environments.
• Working knowledge of U.S. healthcare data domains—including claims, eligibility, and provider datasets—and experience applying this knowledge to complex ingestion and transformation workflows.
• Strong ability to communicate complex technical concepts clearly across both technical and non‑technical stakeholders.
• Expert‑level proficiency in Python, SQL, and PySpark, including developing distributed data transformations and performance‑optimized queries.
• Demonstrated experience designing, building, and operating production‑grade ETL/ELT pipelines using Databricks, Airflow, or similar orchestration and workflow automation tools.
• Proven experience architecting or operating large‑scale data platforms using dbt, Kafka, Delta Lake, and event‑driven/streaming architectures, within a cloud‑native data services or platform engineering environment—requiring specialized knowledge of distributed systems, scalable data pipelines, and cloud‑scale data processing.
• Experience working with structured and semi‑structured data formats such as Parquet, ORC, JSON, and Avro, including schema evolution and optimization techniques.
• Strong working knowledge of AWS data ecosystem components—including S3, SQS, Lambda, Glue, IAM—or equivalent cloud technologies supporting high‑volume data engineering workloads.
• Proficiency with Terraform, infrastructure‑as‑code methodologies, and modern CI/CD pipelines (e.g., GitLab) supporting automated deployment and versioning of data systems.
• Deep expertise in SQL and compute optimization strategies, including Z‑Ordering, clustering, partitioning, pruning, and caching for large‑scale analytical and operational workloads.
• Hands‑on experience with major cloud data warehouse platforms such as Snowflake (preferred), BigQuery, or Redshift, including performance tuning and data modeling for analytical environments.

What we would like to see but not required:

• Experience in large-scale healthcare or payer data environments.

What you’ll get in return :

• Competitive Leave & Benefits
• Comprehensive health coverage
• Equity for every employee – share in our success
• Growth-focused environment – your development matters here

Work arrangements :

• Standard hours: 8 hours/day, 5 days/week
• Location: Pune, Hybrid (3 days a week in office)
• Shift: 12pm-9pm IST

About HG Insights

HG Insights is the pioneer of Revenue Growth Intelligence. For more than a decade, we have delivered comprehensive, AI-driven datasets on B2B buyers, technology adoption, IT spend, and buyer intent, sourced from billions of data points. Today, we are a trusted partner to Fortune 500 technology companies, hyperscalers, and innovative B2B vendors seeking precise go-to-market analytics and decision-making.

Through an evolving suite of AI agents that incorporate first-party data and buyer signals, HG Insights enables AI-powered GTM automation across sales, marketing, RevOps, and data analytics teams, modernizing GTM execution from strategy through activation.

Role Overview

The Applied Data Scientist - Research is a collaborative analytical partner to the Head of Data Science, contributing to the design and validation of GTM insights that power the Contextual Intelligence initiative.

You will co-develop insight logic, selecting signals, designing scoring frameworks, prototyping models in Python, and validating outputs. You will also contribute to the production-ready briefs that are implemented in the data production pipeline by the engineering team.

This role sits at the intersection of statistical modeling, structured data analysis, and applied AI. You are comfortable reasoning about how to measure something rigorously, how entities and relationships in a knowledge graph can be leveraged, and how to use LLMs as a practical tool in the insight development workflow, not as a subject of research, but as part of the toolkit.

What You Will Do

Insight & Model Development

• Co-develop scoring frameworks and metrics models, contributing to signal selection, weighting logic, and model structure across a range of GTM insight types (acquisition,expansion, retention, strategic)
• Prototype insight logic in Python notebooks: assembling features from HG's structured data assets, implementing model components, and stress-testing outputs.
• Design and run validation experiments to confirm that insight outputs are directionally correct, well-calibrated, and meaningful across the full vendor universe
• Contribute to ontology and entity design, thinking through how vendors, products, companies, and relationships should be structured to support a given insight, informed by a conceptual understanding of the knowledge graph schema

Production Brief Development

• Translate insight designs into clear, implementation-ready production briefs 
• Document model specifications precisely: component definitions, feature engineering, aggregation logic, edge case handling, and expected output distributions
• Participate in handoff reviews with the production function, answering implementation questions and refining specs based on feasibility feedback

Insight Research & Discovery

• Contribute to the prioritized insights catalog, researching new insight ideas, assessing data availability, and framing feasibility
• Stay current on GTM data science approaches, competitive intelligence methodologies, and relevant analytical techniques that could expand the insight library

What We're Looking For

Core Skills

• Statistical modeling depth: Ability to design and implement a range of scoring and metrics models from first principles; comfortable with component weighting, normalization, signed rate-of-change metrics, composite aggregation, and distribution analysis; knows when a technique is appropriate and why 
• Python for analytical prototyping: Strong notebook-based Python for data manipulation, feature construction, model prototyping, and output validation; pandas, NumPy, and Scikit are daily 
• SQL: Proficient in querying structured data at scale; used for signal extraction, feature derivation, and validation checks across large vendor and company datasets
• Analytical rigor & validation thinking: Ability to critically evaluate whether a model is measuring what it claims to measure; designs validation experiments, checks edge cases, and flags when outputs don't pass a sanity check
• Clear technical communication: Able to translate analytical logic into precise written specifications; the production brief is a key deliverable 

Applied AI & Graph Literacy

• LLM API usage: Hands-on experience using Claude, GPT, or equivalent APIs as a practical tool; can design effective prompts, integrate LLM steps into an analytical workflow, and evaluate output quality critically
• Knowledge graph concepts: Conceptual understanding of how entities, relationships, and properties are structured in a graph; able to reason about how graph-derived features (e.g., vendor-product-company traversals) should inform insight design, without necessarily writing production Cypher 

Nice to Have

• GTM/Management Consulting, or IT Research experience, familiarity with concepts like install base, intent signals, competitive intelligence, and market analysis. Experience writing Cypher or querying graph-structured data directly
• Experience working collaboratively with engineering, product and GTM teams
• Experience in a B2B SaaS or data products environment

Tools & Environment

Primary

• Python (pandas, NumPy, scipy, Jupyter)
• SQL
• LLM APIs (Claude, GPT)
• Git and version control

Working Knowledge

• Databricks
• Cloud storage 
• Knowledge graph concepts 

About the role

We are seeking an accomplished Data Engineer to join our dynamic and rapidly expanding Tech Ops division. With significant projected growth, this is an opportunity to drive meaningful technical impact. In this role, you will work directly with customers, data vendors, and internal engineering teams to design, implement, and optimize complex data integration solutions within a modern, large‑scale cloud environment.

You will leverage advanced skills in distributed computing, data architecture, and cloud-native engineering to enable scalable, resilient, and high‑performance data ingestion and transformation pipelines. As a trusted technical advisor, you will guide customers in adopting Abacus’s core data management platform and ensure high-quality, compliant data operations across the lifecycle.

Your day to day :

• Architect, design, and implement high-volume batch and real-time data pipelines using PySpark, SparkSQL, Databricks Workflows, and distributed processing frameworks.
• Build end‑to‑end ingestion frameworks integrating with Databricks, Snowflake, AWS services (S3, SQS, Lambda), and vendor data APIs, ensuring data quality, lineage, and schema evolution.
• Develop data modeling frameworks, including star/snowflake schemas and optimization techniques for analytical workloads on cloud data warehouses.
• Lead technical solution design for health plan clients, creating highly available, fault-tolerant architectures across multi-account AWS environments.
• Translate complex business requirements into detailed technical specifications, engineering artifacts, and reusable components.
• Implement security automation, including RBAC, encryption at rest/in transit, PHI handling, tokenization, auditing, and compliance with HIPAA and SOC 2 frameworks.
• Establish and enforce data engineering best practices, such as CI/CD for data pipelines, code versioning, automated testing, orchestration, logging, and observability patterns.
• Conduct performance profiling and optimize compute costs, cluster configurations, partitions, indexing, and caching strategies across Databricks and Snowflake environments.
• Produce high-quality technical documentation including runbooks, architecture diagrams, and operational standards.
• Mentor junior engineers through technical reviews, coaching, and training sessions for both internal teams and clients.

What you bring to the team :

• Bachelor’s degree in Computer Science, Computer Engineering, or a closely related technical field.
• 5+ years of hands‑on experience as a Data Engineer working with large‑scale, distributed data processing systems in modern cloud environments.
• Working knowledge of U.S. healthcare data domains—including claims, eligibility, and provider datasets—and experience applying this knowledge to complex ingestion and transformation workflows.
• Strong ability to communicate complex technical concepts clearly across both technical and non‑technical stakeholders.
• Expert‑level proficiency in Python, SQL, and PySpark, including developing distributed data transformations and performance‑optimized queries.
• Demonstrated experience designing, building, and operating production‑grade ETL/ELT pipelines using Databricks, Airflow, or similar orchestration and workflow automation tools.
• Proven experience architecting or operating large‑scale data platforms using dbt, Kafka, Delta Lake, and event‑driven/streaming architectures, within a cloud‑native data services or platform engineering environment—requiring specialized knowledge of distributed systems, scalable data pipelines, and cloud‑scale data processing.
• Experience working with structured and semi‑structured data formats such as Parquet, ORC, JSON, and Avro, including schema evolution and optimization techniques.
• Strong working knowledge of AWS data ecosystem components—including S3, SQS, Lambda, Glue, IAM—or equivalent cloud technologies supporting high‑volume data engineering workloads.
• Proficiency with Terraform, infrastructure‑as‑code methodologies, and modern CI/CD pipelines (e.g., GitLab) supporting automated deployment and versioning of data systems.
• Deep expertise in SQL and compute optimization strategies, including Z‑Ordering, clustering, partitioning, pruning, and caching for large‑scale analytical and operational workloads.
• Hands‑on experience with major cloud data warehouse platforms such as Snowflake (preferred), BigQuery, or Redshift, including performance tuning and data modeling for analytical environments.

What we would like to see but not required:

• Experience in large-scale healthcare or payer data environments.

What you’ll get in return :

• Competitive Leave & Benefits
• Comprehensive health coverage
• Equity for every employee – share in our success
• Growth-focused environment – your development matters here

Work arrangements :

• Standard hours: 8 hours/day, 5 days/week
• Location: Pune, Hybrid (3 days a week in office)
• Shift: 12pm-9pm IST

ACCOUNTANT

(Pune)

COMPANY OVERVIEW

At Ivalua we are a global community of exceptional professionals, who believe that digital transformation revolutionizes supply chain sustainability and resiliency to unlock the power of supplier collaboration. 

We achieve this through our leading cloud-based spend management platform that empowers hundreds of the world's most admired brands to effectively manage all categories of spend and all suppliers to increase profitability, improve ESG (environmental, social, and corporate governance) performance, lower risk, and improve productivity. Driven by our passions and fueled by our shared ambitions, we empower and challenge each other to create meaningful experiences for our colleagues, customers, partners, and communities. 

 Learn more at www.ivalua.com. Follow us on LinkedIn 

THE OPPORTUNITY

CONTEXT: 

Our Finance department, international in scope (EMEA, AMER, APAC) and in full growth, is made up of around thirty experts. The person will be reporting to the Director, Accounting based in Pune.

ROLE:

We are looking for a detail-oriented and technically proficient Accountant to join our Finance & Accounting team. The ideal candidate will have 3 to 5 years of hands-on experience in Travel & Expense (T&E) processing, end-to-end Accounts Payable invoice management, payroll accounting, and day-to-day accounting operations. In addition, the role requires a strong command of data analysis in accounting contexts and advanced Excel skills, including macro development, to drive process efficiency and reporting accuracy.

WHAT YOU WILL DO WITH US

Travel & Expense (T&E) Processing

• Review, verify, and process employee T&E expense claims in accordance with company policy.
•  Ensure timely reimbursements and accurate recording of expense entries in the accounting system.
• Audit submitted expense reports for compliance, proper documentation, and approvals.
• Liaise with employees and managers to resolve discrepancies or policy violations.

Accounts Payable (AP)

• Manage the complete AP lifecycle from invoice receipt, coding, and PO matching to approval workflow and payment execution.
•  Perform 2-way and 3-way PO matching and resolve invoice discrepancies with vendors and procurement teams.
• Maintain vendor master data, ensure accuracy of payment terms, and process payments via bank transfers and cheques.
• Reconcile AP sub-ledger with the general ledger and resolve open items on a monthly basis.
• Prepare aging reports and support month-end AP close activities.

Day-to-Day Accounting Operations

• Prepare and post journal entries for accruals, prepayments, and other routine accounting transactions.
• Perform bank reconciliations, ledger scrutiny, and balance sheet account reconciliations.
• Support monthly, quarterly, and annual close processes within set deadlines.
• Assist in the preparation of MIS reports, trial balance, and audit schedules.
• Ensure compliance with applicable accounting standards (IND AS / GAAP) and internal controls.
• Assist in the preparation, verification, and processing of monthly payroll for all employees.
• Ensure accurate input of attendance, leave, overtime, deductions, and statutory contributions
• Payroll Accounting journal Entry.

Data Analysis & Reporting

• Analyze financial data to identify trends, anomalies, and cost-saving opportunities.
• Design and maintain Excel-based dashboards, automated reports, and financial models.
• Develop and maintain Excel Macros (VBA) to automate repetitive accounting workflows and enhance productivity.
• Support senior management with ad hoc financial analysis and data-driven insights.

YOUR PROFILE

• If you have the below experience and strengths this role could be for you:

Skills and Experience:

• Minimum 3 years of relevant experience in accounting and finance operations.
• Proven hands-on experience in T&E expense processing, AP invoice processing (end-to-end), payroll processing, and general accounting.
• Demonstrated experience with Excel Macros / VBA automation in an accounting environment.
• Prior exposure to ERP systems such as SAP, Oracle, Tally Prime, or Microsoft Dynamics is preferred.
• B. Com / M. Com or a closely related field or foreign equivalent. 

Soft Skills:

• Strong analytical and problem-solving ability
• High attention to detail and accuracy
• Effective communication and interpersonal skills
• Team player with a proactive work approach
• Strong ethical standards and confidentiality
• Adaptability and continuous learning mindset

WHAT HAPPENS NEXT

If your application fits this specific position’s needs, our skilled Talent team will reach out to schedule an initial screening call. Get one step closer to achieving your goals – apply today! 

Our Talent team will guide you through every step of the interview process - from preparation to completion. They're here to support you! 

Our recruitment process is designed to assess your competencies through a series of personalised interviews with internal stakeholders relevant to the role. 

Interviews will be conducted virtually via video or on-site with face-to-face meetings.

LIFE AT IVALUA

• Hybrid working model (3 days in the office per week),
• We're a team dedicated to pushing the boundaries of product innovation and technology,
• Sustainable Growth, Privately Held,
• A stable and cash-flow positive Company since 10 years,
• Snacks and weekly lunches in the office,
• Feel empowered to pursue your goals with improved team collaboration and increased creativity/productivity,
• Unlock and unleash your full professional potential with our exceptional training and career development program,
• Join a dynamic and international team of top-notch professionals who are experts in their respective fields. Collaborate with like-minded individuals who are deeply passionate and highly motivated about their work. Experience a truly diverse and inclusive work environment where your unique contributions are highly valued,
• Regular social events, competitive outings, team running events, and musical activities,
• Comparably recognized Ivalua for the following (https://www.comparably.com/companies/ivalua) 

Powered by People - Powered by You!

United by our values we embrace diversity and equity in the broadest possible sense to create an inclusive workplace. To help our customers make supply chains more efficient, sustainable and resilient, we rely on a global team with a variety of backgrounds, skills and views. We believe in equal opportunity and in diversity as a driver of innovation that cultivates a spirit of inclusiveness, creates a productive and fun place to work, and provides fulfilling career opportunities for all Ivaluans. 

Experience life at Ivalua - check out our captivating video! Gain insight into our unique company culture and get a glimpse of what it's like to work with us.

#LI-DK1

About the Role

We are looking for a Data Modeler to join a global data modeling team responsible for transforming business requirements into conceptual and logical data models. This role requires understanding of healthcare data domains (Claims, Membership, Enrollment, Provider, Billing, Interoperability - FHIR, HL7, ADT, CCDA, etc.) and experience in enterprise data modeling best practices.

The Data Modeler will work closely with the Director of Data Modeling and Senior Data Modelers to adhere to data modeling standards, metadata governance, and follow data architecture strategies that align with business and technical needs. They will also collaborate with business analysts, product analysts, client implementation teams, and data governance teams to ensure models support operational and analytical use cases, high performance, and data integrity.

This is an exciting opportunity for a data modeler with experience in Databricks, Snowflake, schema evolution, and modern data engineering practices to shape the future of healthcare data platforms.

Your day to day

Identify and define requirements for canonical data models as well as consumption use cases required by enterprise healthcare customers. Your activities will include:

• Perform data profiling analysis.
• Use SQL, data modeling and data integrity principles.
• Build conceptual and logical data models aligned with enterprise architecture, business requirements and industry standards.
• Follow data modeling best practices, including schema evolution, lossless data modeling, metadata management, and data versioning.
• Use enterprise data modeling tools (Erwin, ER/Studio, DBT, or similar).
• Ensure models support analytical (data science, actuarial, reporting) and operational (Claims, Care Management) use cases.
• Maintain metadata, business glossary, entity relationship diagrams and data dictionaries to support data lineage and governance.
• Partner with Client Management, Product, and Business Analyst teams to understand client needs, assess data model impact, and ensure data models and related artifacts meet or exceed expectations.
• Work with client management teams to provide support and data model expertise during client implementation.

What you bring to the team

• 2+ years of experience in data modeling, enterprise data architecture, and cloud-based data engineering.
• Expertise in enterprise data modeling tools (Erwin, ER/Studio, DBSchema, or similar).
• NoSQL data model experience.
• Strong hands-on experience with cloud data platforms (Databricks, Snowflake) and data lakehouse architectures.
• Deep understanding of healthcare data models across Core Payer (Claims, Membership, Enrollment, Provider, Billing, Premium) and Clinical Interoperability (FHIR, HL7, ADT, CCDA, etc.) domains.
• Experience with schema evolution, lossless data modeling, and data versioning strategies.
• Strong background in SQL, data profiling, and metadata creation and maintenance.
• Ability to learn from senior modelers, enforce modeling best practices, and drive adoption of enterprise data standards.
• Excellent collaboration skills to work with data architects, engineers, and client implementation teams.

What we would like to see, but not required

• Healthcare reporting experience.
• Experience with OBT, data lakehouse, and metadata management frameworks.
• Familiarity with business intelligence (BI) and reporting solutions on modern cloud data warehouses.
• Knowledge of APIs, SDKs, and data distribution frameworks for enabling real-time and batch data access.
• Experience with data governance, security, and regulatory compliance in healthcare data management.

What you’ll get in return 

• Competitive Leave & Benefits
• Comprehensive health coverage
• Equity for every employee – share in our success
• Growth-focused environment – your development matters here

Work arrangements 

• Standard hours: 8 hours/day, 5 days/week
• Location: Pune, Hybrid (3 days a week in office)
• Shift: 12pm-9pm IST

About the Role

As a Product Owner in the AI Solutions team, you will play a pivotal role in translating strategic direction into actionable product increments. You will work closely with engineering teams in India, Nepal, and the US to ensure that our generative AI platform delivers measurable value to healthcare payers, with a focus on key business cases (i.e. Payment Integrity) and unstructured data solutions. This is an execution-focused role, responsible for the “how” of delivery and sprint cadence, while closely partnering with the Senior Product Manager who drives the “what” and “why.”

Your day to day

• Create and maintain a structured product backlog for GenAI solutions, ensuring clear problem statements, acceptance criteria, and definitions of done.
• Own GenAI stories in Jira, maintaining distinct boards, sprint cadences, and capacity visibility as defined by team processes.
• Break down high-level product and governance objectives into actionable user stories and tasks.
• Lead grooming sessions with engineers, data modeling, stakeholders, and others to clarify scope, estimate effort, and prioritize work based on business value and readiness.
• Drive sprint planning, coordinate daily stand-ups for the AI team, and proactively remove blockers to ensure commitments are met and deliverables align with the roadmap.
• Define and execute acceptance testing for completed features, verifying that data traceability, outputs, and governance capabilities meet requirements.
• Coordinate with security and compliance to ensure features meet auditability, observability, and hallucination control guardrails.
• Prepare release notes, user guides, and internal training materials; support deployments with DevOps and ensure client-facing documentation reflects new capabilities.
• Act as a liaison between product leadership, engineering, data modeling, and platform teams; communicate progress and issues clearly.
• Track and report on key SDLC metrics (burndown, velocity, throughput, capacity) and maintain a knowledge base of FAQs, lessons learned, and key decisions.
• Champion continuous improvement by applying agile best practices, identifying process bottlenecks, and leveraging AI tools for backlog management and documentation.

What you bring to the team

• 3+ years as a Product Owner or similar role in a data-driven environment, ideally supporting AI, data platforms, or healthcare products.
• Experience working with distributed engineering teams, preferably across US and India time zones, and familiarity with Scrum/Agile methodologies and tools (e.g., Jira, Confluence).
• Demonstrated ability to translate strategic product direction into actionable backlog items, groom stories with engineers, and manage sprint cadence.
• Strong understanding of the software development lifecycle (SDLC) and release management, with the ability to coordinate acceptance testing and quality assurance.
• Exposure to healthcare data (claims, clinical, or payer workflows) and AI/ML technologies.
• Excellent communication and organizational skills; comfortable interfacing with technical and non-technical stakeholders across product, engineering, security, and sales.
• Fluency in English (required for India-based roles).

What we would like to see, but not required

• Experience with healthcare interoperability standards (e.g., HL7 V2, FHIR, X12).
• Experience with cloud technologies (AWS, Azure, GCP), Databricks, or Snowflake.
• Prior work in a high-growth, fast-paced startup environment.

What you’ll get in return 

• Competitive Leave & Benefits
• Comprehensive health coverage
• Equity for every employee – share in our success
• Growth-focused environment – your development matters here

Work arrangements 

• Standard hours: 8 hours/day, 5 days/week
• Location: Pune, Hybrid (3 days a week in office)
• Shift: 12pm-9pm IST

Value Engineer - Pune

The Role

We are looking for a Value Engineer to help scale Showpad’s first formal Value Engineering function. Your mission is to work in partnership with stakeholders listed able to prove the tangible ROI of our software for as many customers as possible. You will be responsible for distilling complex data into compelling financial narratives that demonstrate how Showpad drives revenue, saves time, and develops talent for our 1,400+ global customers.

Reporting to the VP of Revenue Enablement, you will be the bridge between raw data and executive-level business cases, helping our account teams turn customer performance into a quantitative success story.

Key Responsibilities

• Master the Showpad Value Realization Methodology: A framework Showpad GTM is enabled on to empower our ICs to diagnose customer maturity, identify success metrics, and build plans to get high value accounts towards ROI. This methodology will be foundational for the success of the Value Engineering
• Evolve the Value Engineering Blueprint: In partnership with the Revenue Enablement key stakeholders, you will help drive the strategy to scale Showpad’s global Value Engineering function from the ground up by being the analytical and operational backbone to the function.
• Manage the Value Assessment request funnel: In partnership with key Enablement stakeholders, manage the queue of requests for Value Engineering support, based on specific customer and account requirements/qualification. Produce each Value Assessment in accordance with the SLAs committed to Showpad GTM team members.
• Architect ROI Narratives: Translate Showpad platform data and customer-specific performance metrics into high-impact ROI narratives that prove the value of enablement and deliver them in a customer facing capacity as needed
• Operationalize Scalability: Work cross functionally with Enablement and Product Marketing to maintain self-service ROI calculators and value templates
• Full-Lifecycle Value Realization: Support the customer journey by conducting "Value Realization" assessments on an ongoing basis (vs one time events) for specific accounts to ensure customers are hitting KPIs well before the renewal
• Data Translation: Decipher complex, large-scale data sets and transform them into clear, visual, and persuasive narratives for both internal and external
• Strategic Seller Support: Work directly with Account Executives and Customer Success Managers on the value assessment plan and advise Showpad account teams on delivering results to C-suite audiences.
• Technical Subject Matter Expert: Act as a customer-facing expert to answer deep-dive technical questions regarding value assessment methodology and data integrity.
• Product Feedback Loop: Serve as a strategic partner to Product and Engineering, providing data-backed insights on which features are driving the highest measurable Advocate for insights and dashboards that you believe should be in the Product as a result of these findings.
• Fuel Advocacy: Collaborate with Customer Marketing to turn data-driven findings into powerful impact-based case studies and testimonials that fuel the advocacy funnel.

Qualifications

• Data Expertise: Deep background in data You are comfortable diving into large, raw data sets and distilling them into actionable business insights.
• The Track Record: Minimum 2+ years of relevant experience in Value Engineering, GTM Strategy, or a similar data-heavy revenue role.
• The Tech Stack: Proficiency with AWS ǪuickSight, Snowflake, and advanced Excel.
• Enablement Fluency: Familiarity with the Enablement landscape, Sales Tech, or Learning Management Systems (LMS).
• Executive Presence: Ability to remain composed and authoritative when defending complex financial models and ROI claims under scrutiny from executive stakeholders.
• The "Builder" Spirit: A proven track record of designing scalable solutions and a comfort with the ambiguity of building a department from the ground up.
• Collaborator Extraordinaire: This role is highly cross functional and will not own the strategy for the Value engineering function We are looking for a team player who can partner with key stakeholders to scale the Value Engineering function.
• Customer Centricity: A passion for proving Showpad ROI as well as measurable business results coming from Sales, Enablement and Marketing for our customers. Make our customers look great.

About the Role

We are seeking a Senior Data QA Engineer to own and elevate data quality across our data platforms and client solutions. In this role, you will lead complex data validation efforts, shape testing strategies, and act as a trusted partner to Engineering, Product, and Operations. You’ll set standards for data quality, drive automation, and help ensure the delivery of reliable, production‑grade data solutions at scale.

Your Day to Day

• Lead data quality strategy and execution across multiple projects and datasets.
• Partner closely with Engineering, Product, Operations, and Project Management to influence data design and quality outcomes early in the lifecycle.
• Perform advanced data analysis and validation on large‑scale, client‑specific and healthcare datasets.
• Design, execute, and review complex test plans and test cases, including automated and manual testing approaches.
• Identify systemic data quality risks, drive root‑cause analysis, and partner with teams through resolution.
• Define, refine, and document QA standards, best practices, and verification protocols.
• Mentor junior QA engineers and provide guidance on testing methodologies and data validation techniques.
• Contribute to continuous improvement of QA processes, tooling, and workflows.

What You Bring to the Team

• Bachelor’s degree in Computer Science, Health Science, or a related field (or equivalent practical experience).
• 5+ years of experience in data quality, data QA, or testing roles within data‑driven environments; healthcare experience strongly preferred.
• Advanced SQL skills with the ability to validate, troubleshoot, and reason about complex datasets.
• Strong understanding of data pipelines, integrations, and large‑scale data systems.
• Experience working with healthcare data domains such as enrollment, claims, and provider data.
• Demonstrated ability to lead QA efforts, influence cross‑functional teams, and operate with a high degree of ownership.
• Excellent analytical, problem‑solving, and prioritization skills in fast‑moving environments.
• Strong communication skills, with the ability to explain data quality issues and risks to both technical and non‑technical stakeholders.
• Deep understanding of QA methodologies, testing frameworks, and best practices.

What you’ll get in return 

• Competitive Leave & Benefits
• Comprehensive health coverage
• Equity for every employee – share in our success
• Growth-focused environment – your development matters here

Work arrangements 

• Standard hours: 8 hours/day, 5 days/week
• Location: Pune, Hybrid (3 days a week in office)
• Shift: 12pm-9pm IST