Job Title: Technical Lead / Staff Engineer (Backend & Data)
Location: 100% Remote
Duration: 6+ Month Contract
Job Description:
We are seeking a high-level Technical Lead to take an enterprise MVP to a robust, production-grade application for a Fortune 50 company. You will be collaborating with a group of data scientists and optimization engineers to engineer a critical system for business operations. We are currently operating with a mix of Databricks notebooks, Parquet files, and graph databases. Your mission is to lead the consolidation of this environment into a clean, modern stack (FastAPI, Azure Data Factory, PostgreSQL), while enforcing rigorous software engineering standards across the team. You will be expected to make technical decisions considering the trade-offs and challenges faced by the team as we move from MVP to production-grade, enterprise system. You ll need to ensure long-term maintainability without compromising timelines and near-term delivery for a critical product.
Note: This is a pure Technical Lead role. You will lead via code, architecture, and mentorship, not via HR management,
Key Objectives & Responsibilities:
- Backend Architecture & Implementation
Build the Core: Lead the implementation of our backend microservices using
Python (Fast API). You will build the API Gateway, Optimization Service, and Data
Service.
Productionize Optimization Models: Ensure models are integrated via clear
interfaces, deterministic inputs/outputs, reproducible runs, and observable
execution, so that mathematical complexity does not leak into the application
layer.
- ETL Redesign & Consolidation
Untangle the Data: Lead the migration from ad-hoc Databricks notebooks and
disparate storage (Neo4j/Parquet) into a structured pipeline.
Database Strategy: Establish clear database architecture between analytics and
transactional systems to support the product and ensure performance and
maintainability.
- Engineering Culture & Standards
Set the Standard: Enforce Trunk-Based Development, rigorous code reviews,
and clean architecture principles.
Drive DORA: Own and continuously improve our DORA metrics. Optimize for
deployment frequency and low change failure rates.
Mentorship: Act as the technical anchor for the team. Guide mid-level engineers
and optimization specialists on best practices.
Architecture Stewardship: Drive the use of Architecture Decision Records (ADRs)
to document key technical decisions and tradeoffs.
Required Qualifications:
- Experience: 7+ years of software engineering, with specific experience leading technical implementation on complex projects.
- Python Mastery: Deep expertise in modern Python, specifically with FastAPI (Pydantic, AsyncIO).
- Data Engineering: Proven experience architecting ETL pipelines. You have moved messy data landscapes into structured environments using tools like Azure Data Factory and Spark/Databricks.
- SQL & Storage: Strong experience modeling transactional data in PostgreSQL.
- Architecture: Experience designing microservices and API gateways.
- Engineering Rigor: You are a practitioner of CI/CD and Trunk-Based Development. You can explain why these matter to a room of data scientists.
Nice to Have:
- Experience with Gurobi or similar solvers (from an integration/infrastructure perspective, not mathematical).
- Experience with remote-first, distributed teams.
- Familiarity with Azure Kubernetes Service (AKS).
The Tech Stack:
- Backend: Python 3.12+, FastAPI
- Data: Azure Data Factory, Azure Databricks, PostgreSQL
- Infrastructure: Azure, Docker, (Moving to) AKS
- CI/CD: Jenkins
- Optimization: Gurobi (managed by the Opt team, integrated by you)