Senior Forward Deployed Data Engineer
$160,000 to $185,000
Apply (opens in a new tab)Senior Forward Deployed Data Engineer
Posted yesterday
SENIORITY
Senior
SALARY
$160,000 to $185,000
About the role
- Work directly with customer engineers and business stakeholders to understand their workflows, define implementation scope and agree on measurable acceptance criteria.
- Build working prototypes, validate them with customers and develop them into tested, observable production solutions.
- Design and implement data models, pipelines and integrations using SQL and Python across modern cloud data platforms.
- Build and improve agent workflows for development, troubleshooting and testing. Configure the context, metadata and tools they need, with appropriate permissions and safeguards for customer data.
- Review generated code and architecture decisions, investigate failures and implement fixes directly when needed.
- Develop automated tests and evaluations covering business logic, data quality, integration behavior and performance.
- Establish clear boundaries for autonomous action, human approval and escalation. Expand those boundaries as testing and operational evidence demonstrate reliability.
- Own technical delivery through deployment, documentation and handover, helping customers adopt and operate the resulting solutions.
- Identify patterns across customer engagements and turn them into reusable integrations, agent workflows and product improvements with the engineering team.
- Your work will include Duodata implementations and customer data-engineering projects. You’ll stay close to the code, understand how customers use what you build and follow through on delivery.
- What you’ll bring
- Strong SQL skills and practical experience designing maintainable data models and reliable pipelines.
- Production Python experience, including testing, debugging and working with APIs or data integrations.
- Experience delivering solutions on Snowflake, Databricks or a comparable cloud data platform.
- Hands-on experience building or configuring multi-step AI agent workflows for real engineering tasks. You can explain how you supplied context, connected tools, evaluated results and improved reliability.
- The ability to inspect generated code, challenge assumptions and verify that a solution meets its intended business requirements.
- Sound engineering practices around version control, deployment, observability and secure data handling.
- Evidence of owning customer-facing technical work from an ambiguous initial requirement through implementation and handover.
- Clear communication with engineers and business stakeholders, including explaining tradeoffs, managing scope and communicating risks.
- You’re comfortable making decisions with incomplete information and adjusting priorities as you learn. You enjoy working alongside customers, improving how a small team operates and taking responsibility for following through.
Before you apply
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Your profile is current
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Two examples you can talk through
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A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
Employers plan around it, and it's the question that stalls offers most often.
Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.
