Senior Level Data Infrastructure Engineer Jobs
Senior level data infrastructure engineer jobs place experienced engineers in charge of architectural decisions, platform reliability at scale, and the cross-functional teams building the systems that underpin modern data operations. Openings are spread across on-site, remote, and hybrid settings in Technology & Software, Consulting & Professional Services, and Distribution & Wholesale, with Fluidstack, Sezzle, and Connection hiring at this level now.
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Showing 5 of 38+ Senior Level Data Infrastructure Engineer jobs
At Klaviyo, we value the unique backgrounds, experiences and perspectives each Klaviyo (we call ourselves Klaviyos) brings to our workplace each and every day. We believe everyone deserves a fair shot at success and appreciate the experiences each person brings beyond the traditional job requirements. If you're a close but not exact match with the description, we hope you'll still consider applying. Want to learn more about life at Klaviyo? Visit klaviyo.com/careers to see how we empower creators to own their own destiny.
Own the technical direction and delivery for Klaviyo's data platform - streaming, batch compute, storage/lakehouse, and governance - now the foundation for autonomous, agent-driven experiences. Klaviyo's data platform processes billions of events daily across billions of consumer profiles for hundreds of thousands of brands, and increasingly that data is consumed not just by people but by a growing number of AI agents acting on customers' behalf. The footprint grows on two axes at once, ever‑larger data volumes and a steady stream of new data scenarios (new sources, domains, and consumption patterns) and your systems have to scale on both.
You'll design and ship systems that are fast, reliable, cost‑efficient, and safe for autonomous access, creating paved roads for data producers and consumers, human and agent alike. This is an individual‑contributor role (no direct reports); you lead through architecture, code, and influence. Expectations align to Lead/Principal IC behaviors: establishing SLOs, driving technical evolution, and acting as the interface across teams.
What You'll Do
- Design and implement core data platform capabilities (e.g., event ingestion/CDC, stream processing, batch orchestration, data lake/warehouse patterns, catalog/lineage, governance, access, and compliance).
- Define and uphold SLOs for data freshness, availability, and correctness; author/run readiness reviews, incident response, and post‑incident learning for your domain.
- Author ADRs/RFCs, land data contracts and schema governance, and standardize connectors and templates that accelerate developer velocity.
- Profile, tune, and right‑size systems for performance and cost; partner with FinOps on unit‑economics guardrails.
- Pair with product teams and analytics/ML to expose the right abstractions and unblock customer value quickly.
- Contribute high‑quality code and reviews; mentor Staff/ Sr. engineers across pillars through example and enablement (not line management).
- Use AI to streamline data workflows, from authoring and testing pipelines to catalog/search and DQ, so analysts, ML, and product teams move faster with confidence.
Who You Are
- Experience: 10+ years building and operating distributed data systems (e.g., Kafka/PubSub, Flink/Spark/Beam, Airflow/Dagster, Iceberg/Delta/Hudi; Snowflake/BigQuery; object storage) with multi‑tenant reliability.
- Technical expertise: Data ingestion/CDC, stream processing, batch orchestration, lakehouse patterns, catalog/lineage, governance, and access controls, measured by freshness, availability, and correctness SLOs.
- AI tools & automation: You apply ML/GenAI to data platforms - semantic catalog search, auto‑docs, data‑quality anomaly detection, SQL/pipeline generation - with human‑in‑the‑loop review and privacy controls.
- Influence & enablement: You land data contracts, connectors, and templates that speed delivery for producers and consumers; you mentor via design docs and pairing.
- AI fluency (Klaviyo default): You experiment, learn fast, and share AI wins responsibly.
Nice to Haves
- Regional isolation/replication strategies, privacy‑by‑design, and data governance in regulated contexts.
- Adopted paved roads: Producers/consumers are on standard ingestion, processing, and storage paths; schema governance and contracts reduce breakage.
- SLOs & efficiency: 99.9% freshness for key domains; measurable cost/TB reductions; production debugging is faster with defined readiness reviews and incident learning.
- AI‑augmented data operations: Semantic discovery and auto‑documentation cover the majority of high‑value datasets; AI‑assisted DQ monitors reduce data incidents on top pipelines by 25–40%; pipeline authoring and review times drop 15–25% with AI in the loop.
Success in 6 - 12 Months
- Adopted "paved roads" for producers/consumers; 99.9% freshness SLO for key domains; measurable cost/TB reductions.
- One or more step‑change improvements (e.g., 2× faster ingest analytics latency) demonstrated with metrics and post‑incident trend‑down.
This role may require up to 10% travel for purposes such as new hire onboarding, client or partner work if applicable, team meetings, and industry events. Travel is coordinated in advance.
Get to Know Klaviyo
We're Klaviyo (pronounced clay-vee-oh). We empower creators to own their destiny by making first-party data accessible and actionable like never before. We see limitless potential for the technology we're developing to nurture personalized experiences in ecommerce and beyond. To reach our goals, we need our own crew of remarkable creators—ambitious and collaborative teammates who stay focused on our north star: delighting our customers. If you're ready to do the best work of your career, where you'll be welcomed as your whole self from day one and supported with generous benefits, we hope you'll join us.
AI fluency at Klaviyo includes responsible use of AI (including privacy, security, bias awareness, and human-in-the-loop). We provide accommodations as needed.
By participating in Klaviyo's interview process, you acknowledge that you have read, understood, and will adhere to our Guidelines for using AI in the Klaviyo interview Process. For more information about how we process your personal data, see our Job Applicant Privacy Notice.
Klaviyo is committed to a policy of equal opportunity and non-discrimination. We do not discriminate on the basis of race, ethnicity, citizenship, national origin, color, religion or religious creed, age, sex (including pregnancy), gender identity, sexual orientation, physical or mental disability, veteran or active military status, marital status, criminal record, genetics, retaliation, sexual harassment or any other characteristic protected by applicable law.
At Klaviyo, we value the unique backgrounds, experiences and perspectives each Klaviyo (we call ourselves Klaviyos) brings to our workplace each and every day. We believe everyone deserves a fair shot at success and appreciate the experiences each person brings beyond the traditional job requirements. If you're a close but not exact match with the description, we hope you'll still consider applying. Want to learn more about life at Klaviyo? Visit klaviyo.com/careers to see how we empower creators to own their own destiny.
Own the technical direction and delivery for Klaviyo's data platform - streaming, batch compute, storage/lakehouse, and governance - now the foundation for autonomous, agent-driven experiences. Klaviyo's data platform processes billions of events daily across billions of consumer profiles for hundreds of thousands of brands, and increasingly that data is consumed not just by people but by a growing number of AI agents acting on customers' behalf. The footprint grows on two axes at once, ever‑larger data volumes and a steady stream of new data scenarios (new sources, domains, and consumption patterns) and your systems have to scale on both.
You'll design and ship systems that are fast, reliable, cost‑efficient, and safe for autonomous access, creating paved roads for data producers and consumers, human and agent alike. This is an individual‑contributor role (no direct reports); you lead through architecture, code, and influence. Expectations align to Lead/Principal IC behaviors: establishing SLOs, driving technical evolution, and acting as the interface across teams.
What You'll Do
- Design and implement core data platform capabilities (e.g., event ingestion/CDC, stream processing, batch orchestration, data lake/warehouse patterns, catalog/lineage, governance, access, and compliance).
- Define and uphold SLOs for data freshness, availability, and correctness; author/run readiness reviews, incident response, and post‑incident learning for your domain.
- Author ADRs/RFCs, land data contracts and schema governance, and standardize connectors and templates that accelerate developer velocity.
- Profile, tune, and right‑size systems for performance and cost; partner with FinOps on unit‑economics guardrails.
- Pair with product teams and analytics/ML to expose the right abstractions and unblock customer value quickly.
- Contribute high‑quality code and reviews; mentor Staff/ Sr. engineers across pillars through example and enablement (not line management).
- Use AI to streamline data workflows, from authoring and testing pipelines to catalog/search and DQ, so analysts, ML, and product teams move faster with confidence.
Who You Are
- Experience: 10+ years building and operating distributed data systems (e.g., Kafka/PubSub, Flink/Spark/Beam, Airflow/Dagster, Iceberg/Delta/Hudi; Snowflake/BigQuery; object storage) with multi‑tenant reliability.
- Technical expertise: Data ingestion/CDC, stream processing, batch orchestration, lakehouse patterns, catalog/lineage, governance, and access controls, measured by freshness, availability, and correctness SLOs.
- AI tools & automation: You apply ML/GenAI to data platforms - semantic catalog search, auto‑docs, data‑quality anomaly detection, SQL/pipeline generation - with human‑in‑the‑loop review and privacy controls.
- Influence & enablement: You land data contracts, connectors, and templates that speed delivery for producers and consumers; you mentor via design docs and pairing.
- AI fluency (Klaviyo default): You experiment, learn fast, and share AI wins responsibly.
Nice to Haves
- Regional isolation/replication strategies, privacy‑by‑design, and data governance in regulated contexts.
- Adopted paved roads: Producers/consumers are on standard ingestion, processing, and storage paths; schema governance and contracts reduce breakage.
- SLOs & efficiency: 99.9% freshness for key domains; measurable cost/TB reductions; production debugging is faster with defined readiness reviews and incident learning.
- AI‑augmented data operations: Semantic discovery and auto‑documentation cover the majority of high‑value datasets; AI‑assisted DQ monitors reduce data incidents on top pipelines by 25–40%; pipeline authoring and review times drop 15–25% with AI in the loop.
Success in 6 - 12 Months
- Adopted "paved roads" for producers/consumers; 99.9% freshness SLO for key domains; measurable cost/TB reductions.
- One or more step‑change improvements (e.g., 2× faster ingest analytics latency) demonstrated with metrics and post‑incident trend‑down.
This role may require up to 10% travel for purposes such as new hire onboarding, client or partner work if applicable, team meetings, and industry events. Travel is coordinated in advance.
Get to Know Klaviyo
We're Klaviyo (pronounced clay-vee-oh). We empower creators to own their destiny by making first-party data accessible and actionable like never before. We see limitless potential for the technology we're developing to nurture personalized experiences in ecommerce and beyond. To reach our goals, we need our own crew of remarkable creators—ambitious and collaborative teammates who stay focused on our north star: delighting our customers. If you're ready to do the best work of your career, where you'll be welcomed as your whole self from day one and supported with generous benefits, we hope you'll join us.
AI fluency at Klaviyo includes responsible use of AI (including privacy, security, bias awareness, and human-in-the-loop). We provide accommodations as needed.
By participating in Klaviyo's interview process, you acknowledge that you have read, understood, and will adhere to our Guidelines for using AI in the Klaviyo interview Process. For more information about how we process your personal data, see our Job Applicant Privacy Notice.
Klaviyo is committed to a policy of equal opportunity and non-discrimination. We do not discriminate on the basis of race, ethnicity, citizenship, national origin, color, religion or religious creed, age, sex (including pregnancy), gender identity, sexual orientation, physical or mental disability, veteran or active military status, marital status, criminal record, genetics, retaliation, sexual harassment or any other characteristic protected by applicable law.
See All 38 Senior Level Data Infrastructure Engineer Jobs
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Find JobsSenior Level Data Infrastructure Engineer Job Market
Who's Hiring
- Fluidstack4
- Sezzle4
- Connection3
- Nuro2
- Oracle2
Top Industries Hiring
- Technology & Software22
- Consulting & Professional Services4
- Distribution & Wholesale3
- Retail2
- Electronics & Hardware2
Senior Level Data Infrastructure Engineer Jobs: Frequently Asked Questions
How do I get a senior level data infrastructure engineer job?
Employers hiring at the senior level want candidates who have owned production infrastructure end-to-end, not just contributed to it. Demonstrating that you have designed and shipped systems at scale, made architectural trade-off decisions, and mentored junior engineers gives you a clear edge. Highlight specific outcomes: reduced latency, improved pipeline reliability, or cost savings driven by your technical choices.
Which companies hire senior level data infrastructure engineers?
Companies hiring senior level data infrastructure engineers right now include Fluidstack, Sezzle, and Connection, based on current listings on Migrate Mate as of July 2026. Hiring at this level tends to come from organizations with complex, high-volume data environments where platform ownership and technical leadership are core to the role.
Are there remote senior level data infrastructure engineer jobs?
Yes, remote and hybrid opportunities are a meaningful share of the market at this level. About 25% of senior level data infrastructure engineer openings are remote or hybrid as of July 2026, reflecting how many engineering organizations have built distributed infrastructure teams. On-site roles do exist, particularly at companies with strict data security or compliance requirements.
What makes a data infrastructure engineer role senior level?
Senior level roles are defined by ownership and scope rather than task execution. You are expected to set the technical direction for data platforms, make architectural decisions that affect multiple teams, and be accountable for system reliability and scalability in production. Mentoring junior and mid-level engineers and partnering with data science, analytics, and product teams on platform strategy are also standard expectations.
Which industries hire the most senior level data infrastructure engineers?
Senior Level data infrastructure engineer roles concentrate in Technology & Software, Consulting & Professional Services, and Distribution & Wholesale, based on current listings on Migrate Mate as of July 2026. These sectors tend to operate at data volumes and pipeline complexity that require experienced engineers who can own infrastructure decisions rather than follow established playbooks.