Overview:
Medallia is the pioneer and market leader in Experience Management. Our award-winning SaaS platform, Medallia Experience Cloud, leads the market in the management of experiences, insights, and actions for candidates, customers, employees, patients, and residents alike.
We believe that every experience is a memory that can last a lifetime. Experiences shape the way people feel about a company. And they greatly influence how likely people are to advocate, contribute, and stay. At Medallia, we are committed to creating a world where organizations are loved by their customers and their employees.
We empower exceptional people to create extraordinary experiences together.
Bring your whole self.
The Role and Team
The Nexus Data Platform team owns the ETL data pipeline and analytical engine that powers Medallia's next-generation reporting and analytics experience. We build and operate the centralized data platform that gives every Medallia product a shared, reliable view of the customer — one source of truth for who they are and how they've engaged across offerings. This is platform engineering: pipelines, contracts, and serving infrastructure at scale.
Responsibilities:
- Set technical direction for the platform's analytical serving layer — storage topology, ingest from streaming contracts, and partitioning for multi-tenant workloads.
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Own OLAP serving strategy end-to-end: engine topology, ingest patterns from upstream streaming contracts, and benchmark-driven SLA gates for tenant- and program-scoped reporting workloads.
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Define the contract boundary between upstream ETL and the analytical serving layer — what the serving layer consumes, how records unify across sources, and how new data sources are projected in.
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Lead production hardening of the serving layer — deployment architecture, operator lifecycle, security, and observability under real load.
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Represent the analytical serving layer in cross-team forums with product, reporting, and analytics partners — resolving ambiguity at contract boundaries before it becomes delivery risk.
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Mentor senior engineers on OLAP schema design, query optimization, and operational practices for the serving layer.
Candidates based in the Buenos Aires or Mexico City vicinity will be prioritized as this role is Hybrid, 3 days per week onsite.
Qualifications:
Minimum Qualifications
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10+ years building and operating large-scale analytical/OLAP serving systems in production.
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Hands-on experience operating an OLAP or analytical serving engine at scale (StarRocks, Clickhouse, Druid, or similar) — schema design, ingest, and query-performance tuning under multi-tenant load.
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Demonstrated track record of serving-layer architecture design for multi-tenant SaaS workloads — partition strategy, tenant/program-scoped read and write SLA tradeoffs, and hot-partition mitigation.
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Fluency in analytical schema design and evolution, including migrations at scale.
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Working fluency in how data arrives from upstream streaming systems — enough to define and defend ingest contracts, without needing to own those pipelines yourself.
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Ability to write clear ADRs, runbooks, and onboarding docs that keep a fast-moving team aligned without bureaucracy.
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Track record mentoring senior engineers and influencing technical direction beyond your immediate team.
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Professional working English proficiency, written and oral.
Preferred Qualifications
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Hands-on experience with StarRocks at scale — Routine Load, Stream Load, FE/BE topology, and query-pattern tuning; ClickHouse, Druid, Pinot, or other comparable OLAP engines also considered strong experience.
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Apache Iceberg operations — Nessie or Hive/Glue catalog, S3-backed tables, Flink sink configuration.
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Gov Cloud or regulated-environment awareness for data platform deployments.
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Direct experience with Kafka, Flink, or CDC tooling (e.g. Debezium) — useful for reasoning about upstream contracts, though not required to own.
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Familiarity with Medallia’s domain (experience management, survey lifecycles, program/tenant hierarchies) or an equivalent multi-tenant feedback platform.
How We Work
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AI-assisted development — we use coding agents and automation to move fast; you should be comfortable reviewing and directing AI-generated changes, not writing every line by hand.
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Local-first iteration — every engineer has a local stack to develop and test pipeline changes before promoting to shared environments; schema and job work should be fast to try without waiting on central infrastructure.
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Prove it before you ship — automated smoke tests and performance benchmarks are part of how we validate changes, not a handoff to someone else at the end.
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Cross-team by design — data contracts between platform and product teams are explicit; we coordinate early with external teams so downstream consumers stay aligned without slowing delivery.
What Success Looks Like in the First 6 months
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Published architectural decisions for the analytical serving layer’s most pressing open questions — with partner-team sign-off and a clear path to implementation.
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Serving-layer performance meeting agreed thresholds for tenant- and program-scoped workloads on at least one onboarded domain.
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Production infrastructure path for the serving layer defined and partially executed — topology, deploy gates, and upgrade strategy documented and exercised.
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A cross-team ingest contract shipped with SLA baselines a downstream reporting team can rely on.
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Team operating more smoothly — senior engineers more autonomous on OLAP schema and query work, fewer recurring surprises.
At Medallia, we celebrate diversity and recognize the value it brings to our customers and employees. Medallia is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age (40 and over), disability, genetic information, veteran status or military service, or any other status protected by state or local law. Individuals with a disability who need an accommodation to apply please contact us at
[email protected]. For information regarding how Medallia collects and uses personal information, please review our Privacy Policies. Applications will be accepted for 30 days from the date this role was posted or until the role has been filled.
