Technical Lead / Staff Engineer (Backend & Data)

Job Details:

Job Title:             Technical Lead / Staff Engineer (Backend & Data)

Location:             100% Remote

Duration:             6+ Months

Client: Fortune 50

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:

1. 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.

2. 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.

3. 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)