Strong knowledge of various data sources, integration patterns (APIs, web scraping, messaging queues), and ETL/ELT tools. * Expertise in programming languages such as Java, Python, Scala, or Go.
Strong knowledge of various data sources, integration patterns (APIs, web scraping, messaging queues), and ETL/ELT tools. * Expertise in programming languages such as Java, Python, Scala, or Go.
Strong knowledge of various data sources, integration patterns (APIs, web scraping, messaging queues), and ETL/ELT tools. * Expertise in programming languages such as Java, Python, Scala, or Go.
Strong knowledge of various data sources, integration patterns (APIs, web scraping, messaging queues), and ETL/ELT tools. * Expertise in programming languages such as Java, Python, Scala, or Go.
Python Data Scraping information
What is the difference between Python Data Scraping vs Python Data Analysis?
| Aspect | Python Data Scraping | Python Data Analysis |
|---|---|---|
| Primary Focus | Extracting data from websites and online sources | Processing, interpreting, and visualizing data |
| Skills Required | Web scraping libraries (BeautifulSoup, Scrapy), Python programming | Data manipulation (Pandas), statistical analysis, visualization (Matplotlib, Seaborn) |
| Work Environment | Data collection, often in research or data-driven companies | Data interpretation, reporting, and decision-making |
| Common Usage | Gathering data for research, market analysis, or machine learning | Business insights, data reporting, predictive modeling |
Python Data Scraping and Python Data Analysis are related but distinct roles. Data scraping focuses on extracting data from websites, while data analysis involves processing and interpreting that data. Both require Python skills but serve different stages of the data pipeline.
Full-time
Medical, Dental, Vision, Life, Retirement, PTO
Posted 16 days ago
WEX Inc. rating
7.5
Based on 15 frontline employees who took The Breakroom Quiz
10th of 17 rated payment service providers
Job description
This is a remote position; however, the candidate must reside within 30 miles of one of the following locations: Portland, ME; Boston, MA; Chicago, IL; Dallas, TX; San Francisco Bay Area, CA; and Seattle/WA.
About the Team/Role
As WEX continues to scale its Data-as-a-Service (DaaS) platform, the Data Acquisition Team plays a critical role in enabling secure, scalable, and reliable ingestion of data from hundreds of internal systems and external sources.
We are seeking a hands-on Senior Manager, Software Engineering - Data Acquisition to lead our team in acquiring and processing high-volume data, while simultaneously driving the evolution toward AI-augmented, spec-driven software development to enhance platform scalability and delivery speed.
This role requires a strong leader with deep technical expertise in data pipelines, distributed systems, and cloud architecture, who can drive technical excellence, foster a culture of innovation, and align the data acquisition strategy with overall business goals.
Responsibilities:
Engineering Leadership & Team Development: Recruit, mentor, and lead a high-performing team of software engineers focused on data acquisition, fostering a collaborative and inclusive culture. Oversee performance management, career pathing, and top-tier talent acquisition.
AI-Augmented Development Strategy: Pioneer the adoption of AI-assisted software development across engineering teams. Define metrics and implement AI-enabled development workflows to measurably enhance engineering productivity.
Specification-Driven Development (SDD): Establish and enforce a specification-first development methodology. Standardize templates for all key artifacts (APIs, data contracts, ingestion pipelines, architecture) and ensure end-to-end traceability across implementation, validation, deployment, and observability.
Architectural Transformation & Modernization: Drive the migration to automated, metadata-driven, and declarative engineering architectures. Develop reusable frameworks that translate technical specifications directly into generated code, deployment artifacts, and operational controls.
Strategic Roadmap Execution: Define and execute the technical roadmap for all data acquisition pipelines and systems, ensuring the infrastructure is highly scalable, reliable, secure, and cost-effective to accommodate accelerating data volume and velocity.
Technical Governance & Oversight: Provide authoritative technical direction on the design, development, and maintenance of mission-critical data ingestion frameworks. Mandate and enforce best practices for software engineering, data governance, and data quality.
Stakeholder Collaboration: Partner closely with Product Management, Data Science, Data Governance, and other engineering teams to align data solutions with overarching business requirements and strategic data needs.
Engineering Process Optimization: Institute and champion continuous improvement in engineering processes, tools, and methodologies, including CI/CD, automation, monitoring, and alerting practices.
Sustained Operational Excellence: Guarantee the high availability and performance of all data acquisition systems, taking ownership of incident response, recovery, and thorough root cause analysis for major service disruptions.
Resource & Financial Stewardship: Oversee budget allocation, resource management, and capacity planning to ensure the strategic growth of the data acquisition organization.
Qualifications:
Education: Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.
Experience: 10+ years of experience in software engineering, with at least 5+ years in a management role overseeing software engineering or data acquisition teams.
Experience in leading virtual teams is highly desirable
Technical Expertise:
Experience implementing AI-assisted engineering workflows in production software organizations.
Deep understanding of specification-driven engineering, declarative system design, or model-driven development.
Deep expertise in building and managing high-volume, real-time and batch data pipelines (e.g., Kafka, Kinesis, Pulsar).
Proficiency with cloud platforms (e.g., AWS, Azure, GCP) and experience designing scalable, serverless, or containerized data ingestion architectures (e.g., Kubernetes, EKS/AKS/GKE).
Strong knowledge of various data sources, integration patterns (APIs, web scraping, messaging queues), and ETL/ELT tools.
Expertise in programming languages such as Java, Python, Scala, or Go.
Solid understanding of database technologies (SQL, NoSQL, Data Warehouses like Snowflake, Redshift, etc.).
Leadership Skills: Proven ability to lead, motivate, and manage multiple distributed teams. Excellent communication, presentation, and interpersonal skills.
Problem Solving: Strong analytical and problem-solving skills, with the ability to define solutions for complex technical challenges.
About WEX
Sourced by ZipRecruiter
Industry
Software development
Company size
1,001 - 5,000 Employees
Headquarters location
Portland, ME, US
Year founded
1983