Senior Solutions Architect (Remote - Brazil)

nexla; United States; Remote; USD 140,000 - 190,000; Full time

Job summary

Nexla is seeking a Solutions Architect to own the technical relationship with a portfolio of customers in the United States. You will guide onboarding, design integrations, and translate complex technical details to diverse audiences, from data engineers to VPs. You’ll mentor teammates and partner with CSM and Support on renewals and expansion signals.

The role emphasizes communication, trust-building, and the ability to push back on requirements while keeping expectations aligned with reality.

Qualifications

• Communication and customer ownership lie at the core of the role.
• Explain technical concepts to non-technical stakeholders without dumbing down.
• You handle conflict without escalating it and keep the relationship intact.
• You build trust over months and are someone customers ask for by name.
• You write clearly: summaries, next steps, and owners after calls.
• You raise problems early, including your own, to avoid surprises.
• You push back on bad requirements to protect outcomes.

Responsibilities

• Own the technical relationship for a portfolio of accounts and maintain continuity.
• Lead onboarding and implementation, guiding integration to production.
• Run tough conversations and keep credibility with a next-step plan.
• Flag risk early in writing and escalate as needed with context.
• Translate between data engineers, security reviewers, and VPs without losing nuance.
• Troubleshoot with customers: failed runs, schema drift, auth issues, connectivity.
• Partner with CSM and Support on renewal risk and expansion signals to Sales.
• Mentor other SAs on customer handling and problem resolution.

Skills

Communication

Customer ownership

Non-technical explanation

Conflict management

Trust building

Clear writing

Problem raising

Requirements pushback

Python

SQL

Data pipelines

Cloud data platforms

Authentication

Networking

Job description

Nexla, briefly

Nexla is the data connectivity layer for enterprise AI. Over 1,000 bidirectional connectors give agents real-time access to data and actions over MCP. Nexla's Agentic Data Integration handles high-volume streaming ETL, CDC, and Document ETL. At the core of the platform is Helix, a context engine that continuously learns from metadata, schemas, telemetry, and documentation to give agents accurate context and keep pipelines reliable. Nexla processes over a trillion records a month for enterprises including DoorDash, LiveRamp, LinkedIn, and J&J. Honorable Mention in the Gartner Magic Quadrant™ for Data Integration Tools, and top-rated by customers on Gartner Peer Insights four years running.

About the role

You’ll own the technical relationship with our accounts: onboarding, implementation, adoption, escalations, and everything that happens when a pipeline that used to work stops working.

You are the person the customer’s data team calls, and the person who tells them the truth when the answer is inconvenient. Most of the job is conversation: understanding what they are actually trying to do, explaining what the platform will and will not do for them, keeping their expectations aligned with reality, and raising problems while they are still small.

The technical part matters, but not in the way people usually assume. We want a generalist who has built things before and therefore understands how the pieces fit together: what a Kubernetes cluster is for, why a VPN tunnel might be the bottleneck, what a stack trace is telling you, what a slow query looks like. You will not be asked to be the deepest engineer in the room. You will be asked to be the person who can talk to the deepest engineer in the room, understand them, and translate what they said to a VP who has thirty seconds.

What you will do

• Own the technical relationship for a portfolio of accounts. You are the continuity: the person who knows their environment, their history, and their constraints.
• Lead onboarding and implementation. Understand what the customer is trying to build, design the integration with them, and guide it to production.
• Run the hard conversations. A missed date, a degraded pipeline, a limitation they did not expect, a customer who is upset and technically wrong. You stay calm, keep credibility, and land on a next step everyone agrees to.
• Flag risk early and in writing. Adoption stalling, a champion who left, a project quietly losing sponsorship, an architecture heading somewhere that will not scale. Flagging a risk three weeks early is worth more here than fixing it heroically after it lands.
• Translate between audiences. The same situation explained to a data engineer, to a security reviewer, and to a VP, without losing any of them.
• Troubleshoot alongside the customer: failed runs, schema drift, connector and authentication failures, connectivity problems, performance issues. You do the first‑line diagnosis and bring engineering a clear reproduction when it needs to escalate.
• Partner with CSM and Support on renewal risk, and hand expansion signals to Sales.
• Mentor other SAs on how to handle customers, not just how to solve problems.

What you need

• Communication and customer ownership (the core of the role)
• You can explain a technical concept to a non-technical stakeholder without either dumbing it down or losing them.
• You handle conflict without escalating it. You can tell a customer no, or “that was our mistake” and keep the relationship intact.
• You build trust over months, not meetings. Customers should ask for you by name.
• You write clearly and unprompted: summaries, next steps, and owners after every meaningful call.
• You raise problems early, including your own. We would much rather hear “this is slipping and here is why” than a confident status update that turns out to be wrong.
• You push back on bad requirements instead of silently building them.

Technical breadth

• Python. You can read someone else’s script, follow what it does, make a modification, and understand stack traces.
• SQL. Comfortable writing joins, aggregations, and filters. You can look at a slow query and have a sensible first guess about why.
• Data pipelines and integration. APIs and their common failure modes (rate limits, pagination, retries, auth expiry), webhooks, CDC, file-based ingestion, batch versus streaming trade‑offs.
• Cloud data platforms. Working familiarity with at least one of Snowflake, Databricks, BigQuery, Redshift, or a major cloud data warehouse.
• Authentication. You understand what OAuth, SSO, service accounts, and API keys are and roughly how they work. You can follow a conversation about a failing token exchange.
• Networking. DNS, firewalls, private connectivity, VPN