What are the responsibilities and job description for the Senior Engineer position at NexusOne?
About Nexus
You don't have an AI story if you don't have your data story. That's where NexusOne comes in.
We're the converged data platform for the AI era — composable by design, built on an open-source foundation, and AI-native from the ground up. One identity, one governance envelope, one operational layer across every mainframe, data lake, warehouse, and streaming system in the business. For the first time, enterprises can bring their existing stack along instead of rebuilding it — and still give AI agents full context across the estate.
What we stand for is simple: sovereign data, interoperable systems, decoupled intelligence — delivered the way modern software should be. No rip-and-replace. No multi-year transformation. Our CEO Anu Jain puts it well: we turn the "ball of yarn" of data integrations into a unified engine — less like assembling car parts, more like buying the car ready to drive. 85 open-source tools pre-integrated. AI-native automations that deploy and self-heal the stack without human toil. Forward-deployed engineers who build shoulder-to-shoulder with customer teams — hands on keyboards, not just on decks.
It's working, and fast. We're tripling revenue year over year, backed by Insight Partners, and running in production in environments most vendors won't touch. Our platform processes credit risk data for 90% of US small businesses — 40M — every month. Intent signals for 300M subscribers monthly for Africa's largest telco. The data and AI layer for a Top 3 US bank.
We're 100 people across the US and India, headquartered in Atlanta. We think big, move fast, and don't mistake activity for progress. We hire people who'd rather ship the rocket than brief someone on it.
Check out this podcast of Anu talking about our solution here: https://www.youtube.com/watch?v=g8g50sv5GhQ
We're looking for a Senior Engineer to design, build, and maintain the data infrastructure that powers analytics, reporting, and product features across the company. You'll work closely with engineering, analytics, and business stakeholders to turn raw data into reliable, well-modeled, and accessible datasets. This role is a strong fit for someone who enjoys owning pipelines end-to-end and who cares as much about data quality and reliability as about building new capability.
Key Responsibilities
At Nexus, we value people who want to grow — and support each other while doing so.
You can expect:
If this role sounds like a great fit — or even close to one — we’d love to hear from you. We know that no candidate checks every single box, and we’re excited to meet people who bring curiosity, talent, and a desire to build meaningful work together.
You don't have an AI story if you don't have your data story. That's where NexusOne comes in.
We're the converged data platform for the AI era — composable by design, built on an open-source foundation, and AI-native from the ground up. One identity, one governance envelope, one operational layer across every mainframe, data lake, warehouse, and streaming system in the business. For the first time, enterprises can bring their existing stack along instead of rebuilding it — and still give AI agents full context across the estate.
What we stand for is simple: sovereign data, interoperable systems, decoupled intelligence — delivered the way modern software should be. No rip-and-replace. No multi-year transformation. Our CEO Anu Jain puts it well: we turn the "ball of yarn" of data integrations into a unified engine — less like assembling car parts, more like buying the car ready to drive. 85 open-source tools pre-integrated. AI-native automations that deploy and self-heal the stack without human toil. Forward-deployed engineers who build shoulder-to-shoulder with customer teams — hands on keyboards, not just on decks.
It's working, and fast. We're tripling revenue year over year, backed by Insight Partners, and running in production in environments most vendors won't touch. Our platform processes credit risk data for 90% of US small businesses — 40M — every month. Intent signals for 300M subscribers monthly for Africa's largest telco. The data and AI layer for a Top 3 US bank.
We're 100 people across the US and India, headquartered in Atlanta. We think big, move fast, and don't mistake activity for progress. We hire people who'd rather ship the rocket than brief someone on it.
Check out this podcast of Anu talking about our solution here: https://www.youtube.com/watch?v=g8g50sv5GhQ
We're looking for a Senior Engineer to design, build, and maintain the data infrastructure that powers analytics, reporting, and product features across the company. You'll work closely with engineering, analytics, and business stakeholders to turn raw data into reliable, well-modeled, and accessible datasets. This role is a strong fit for someone who enjoys owning pipelines end-to-end and who cares as much about data quality and reliability as about building new capability.
Key Responsibilities
- Design, build, and maintain scalable ETL/ELT pipelines that ingest, transform, and deliver data from a variety of internal and external sources
- Develop and optimize data models and schemas that support analytics, reporting, and downstream application needs
- Monitor pipeline health, troubleshoot data quality issues, and implement alerting and observability practices
- Partner with analytics, product, and engineering teams to understand data needs and translate them into durable data solutions
- Improve performance, scalability, and cost-efficiency of existing data infrastructure
- Write clear technical documentation and contribute to team standards for testing, code review, and deployment
- Participate in on-call or incident response rotations as needed to support production data systems
- 4 years of professional experience in data engineering or a closely related discipline
- Strong proficiency in SQL and at least one programming language commonly used for data engineering (e.g., Python, Scala, or Java)
- Hands-on experience building and operating ETL/ELT pipelines in a production environment
- Experience working with cloud data platforms (e.g., AWS, GCP, or Azure) and modern data warehousing tools
- Solid understanding of data modeling, data quality, and pipeline orchestration concepts
- Comfort working with large, complex datasets and diagnosing data issues independently
- Experience with orchestration tools such as Airflow, Dagster, or similar
- Familiarity with streaming data technologies (e.g., Kafka, Kinesis)
- Experience with dbt or similar transformation frameworks
- Exposure to infrastructure-as-code practices (e.g., Terraform)
- Prior experience supporting analytics or data science teams directly
At Nexus, we value people who want to grow — and support each other while doing so.
You can expect:
- A collaborative team culture built on curiosity and respect
- Challenging work where your contributions clearly matter
- A leadership team that invests in learning and development
- The opportunity to work at the intersection of cloud, data, and AI innovation
If this role sounds like a great fit — or even close to one — we’d love to hear from you. We know that no candidate checks every single box, and we’re excited to meet people who bring curiosity, talent, and a desire to build meaningful work together.