Senior Data Engineer

FinStrat Management · India, Philippines · posted 689mo ago

Listing supplied by Himalayas. 101 Careers did not originate this post and applications are handled by the employer.

About this role

The Role

FSM is building the next generation of AI-powered financial systems — where accounting, operations, and data applications work together intelligently. As a Senior Data Engineer, you'll be both a core builder of that platform and a primary technical point of contact for clients as they navigate that transformation.

This is a hands-on, client-facing, senior engineering role. Most of your week is deep technical work — cloud infrastructure, data pipelines, and AI agents. A meaningful part of it is direct conversation with client accounting, finance, and operations teams, leading discovery and translating what you learn into what we ship. You're equally comfortable debugging an IAM policy, pairing with an AI Agent Engineer, and running a discovery session with a client's Controller.

You'll work closely with the Head of Engineering and CTO, alongside FSM's junior and senior engineers and offshore team, and serve as a trusted technical voice clients rely on throughout the engagement.

What You'll Do

1. Cloud & Platform Engineering — the foundation

Design, build, and operate FSM's AWS infrastructure: Lambda, API Gateway, SQS, RDS, Cognito, Secrets Manager, CloudWatch.
Own infrastructure-as-code (CloudFormation), CI/CD (GitHub Actions), and our multi-tenant security model — IAM roles, tenant isolation, secrets management, auditability.
Maintain FSM's security and compliance posture — least-privilege IAM, secrets management, and ongoing SOC 2 / Vanta controls, checks, and audit readiness.
Maintain and extend our templating/scaffolding system (copier-based) so new client pipelines and agents deploy fast and stay consistent.

2. Data Engineering & Integration

Build and maintain data pipelines and the S3-based data platform feeding our agents and BI (DBT, AWS QuickSight).
Architect and build integrations across accounting, ERP, CRM, and operational apps — QuickBooks, HubSpot, Stripe, Plaid, Box, Slack — into a clean, source-agnostic layer.
Ensure consistent, accurate, reconciled data flow.

3. Agent Development & Implementation

Design and code intelligent agents that act on financial data through APIs and natural-language interfaces, plugging into FSM's orchestration layer.
Develop the logic frameworks, contracts, and prompts that govern how agents interpret data, take action, and communicate results — including human-in-the-loop controls.
Test and refine agent performance with real client data — ensuring security, auditability, and alignment with accounting principles.
Client-facing: Walk clients through agent behavior and outputs directly, building their confidence and trust in the automation.

4. Client Discovery & Problem Definition

Client-facing: Lead discovery sessions with client accounting, finance, and operations teams to understand their workflows, data challenges, and automation needs.
Serve as the primary technical liaison between FSM and the client — explaining findings, options, and trade-offs in terms non-technical stakeholders can act on.
Identify opportunities where AI agents can replace repetitive processes, improve reconciliation, or enhance insight delivery.
Translate accounting concepts into technical requirements — and technical constraints back into business terms.

5. Documentation, Standardization & Communication (a real, weighted part of the job — not an afterthought)

Create comprehensive documentation of automations, agent behaviors, infrastructure, and client-specific implementations.
Establish repeatable playbooks, naming conventions, and frameworks that take us from trial-and-error to scalable structure.
Partner with leadership to define best practices as the department evolves.
Share progress, blockers, and technical decisions clearly — and early — across Engineering, Client Delivery, and CSM, not just with the AI Agent Engineering team.

Requirements

5+ years building and operating production systems on AWS, with real depth in serverless (Lambda/API Gateway), infrastructure-as-code (CloudFormation or similar), and cloud security (IAM, secrets, multi-tenancy).
Strong data engineering: Python, SQL, data pipelines, and a modern data stack (DBT, S3/data-lake patterns, a BI tool).
Solid CI/CD and Git discipline; you write reviewable code and review others' well.
Experience integrating accounting/ERP/CRM platforms (QuickBooks, HubSpot, or similar) via APIs, webhooks, or connectors.
Comfort with LLM-based tools and APIs — prompt design and evaluating agent outputs for accuracy and reliability.
Hands-on experience using AI coding tools (e.g., Claude Code) as part of your daily development workflow — planning, building, reviewing, and documenting code with them.
Demonstrated experience working directly with clients or business stakeholders — leading discovery, presenting findings, managing expectations, not just coding behind the scenes.
You take positions and own decisions. Under ambiguity you form a recommendation, explain your reasoning, and drive it — rather than waiting to be told.
You communicate clearly under pressure — status, trade-offs, and blockers surfaced early — with technical and non-technical audiences alike.
Excellent verbal and written English; strong overlap with US Eastern hours.

Bonus Points:

Experience building LLM/AI agents or orchestration systems.
Templating tools (copier/cookiecutter).
Working knowledge of accounting (reconciliations, journal entries, chart of accounts, financial reporting) — or a genuine willingness to learn the domain; we'll teach it.
Experience taking a team from bespoke work toward standardized, documented process.
Familiarity with SOC 2 / Vanta-style compliance.

Our Stack

AWS (Lambda, API Gateway, SQS, RDS + RDS Proxy, Cognito, Secrets Manager, CloudFormation, CloudWatch) · Python · GitHub Actions · Claude Code · copier · DBT · S3 · AWS QuickSight · LLM agents (Claude) · QuickBooks, HubSpot, Stripe, Plaid, Box, Slack

What Success Looks Like

Clients trust you as a technical partner, not just a vendor resource - they bring you problems before they bring you requirements.
Discovery sessions consistently surface automation opportunities that convert into shipped agents and integrations.
The platform you build is secure, multi-tenant, and reliable - deployments are repeatable and don't bottleneck on any one person.
Internal teams (Engineering, Client Delivery, CSM, Leadership) have clear visibility into your work through documentation and proactive communication.
Agent deployments are accurate, auditable, and aligned with sound accounting principles — earning continued client confidence.
Security and compliance stay audit-ready - SOC 2 / Vanta controls and checks are maintained without last-minute fire drills.