Staff Engineer – Data Engineering

Jobtailor; Arizona; On-site; USD 140,000 - 190,000; Full time

Job summary

Jobtailor in the United States is seeking a senior Data Platform Architect to design and implement scalable data systems across cloud environments. Collaborate with product teams to translate complex data needs into robust architectures, while guiding the lifecycle from design through production delivery.

The ideal candidate has extensive experience with data warehouses, big data, AI/ML model lifecycle, and modern data tooling.

Qualifications

• Bachelor's degree in computer science or related technical field.
• Eight+ years of relevant related experience.
• 7+ years in complex data platform, distributed systems, SaaS, cloud solutions, microservices.
• 6+ years in Data Warehouse, Big Data, real-time & batch processing, data standards.
• 4+ years in Business Intelligence solutions.
• 2+ years in AI/ML model development lifecycle.
• Experience delivering business-critical systems to market.
• Ability to influence and work in a collaborative team environment.
• Experience designing/developing scalable systems.
• Extensive experience with Data Warehouse (Star/Snowflake), SQL Server, Big Data stacks (HDFS, ElasticSearch), ETL with IBM Infosphere, reusable frameworks.
• Experience with Python, Spark, PySpark, R, DataRobot.
• Experience with event-driven architectures and messaging (Pub/Sub, Kafka, RabbitMQ).
• Cloud proficiency (GCP, AWS, Azure).
• Knowledge of CI/CD, testing, secure coding, SDLC, Agile/LEAN, DevOps.
• Attention to detail and strong analytical skills.

Responsibilities

• Build data strategy for broad or complex requirements extending beyond the direct team.
• Participate in strategic development of methods, techniques, and evaluation criteria for projects and programs.
• Drive data architecture, design, prototyping and implementation for product needs and data strategy.
• Provide leadership in building a technical plan and backlog, guiding execution to production delivery.
• Lead a broad functional area and coordinate with team members for planning.
• Represent engineering in cross-functional sessions and advocate sound arguments.
• Influence others to reach agreement or behavior changes.
• Collaborate with product managers, designers, and other engineering groups to build new features.
• Own features or systems and maintain long-term health of related systems.
• Support Support and Operations teams in resolving production issues quickly.
• Develop and implement tests for quality, performance, and scalability.
• Continuously improve engineering data standards, tooling, and processes.
• Contribute to risk management and data confidentiality.

Skills

8+ yrs data platform

BI Solutions

AI/ML Development

Business-critical delivery

Cross-functional influence

Scalable systems design

Python

Spark

R

DataRobot

Event-Driven Architecture

Cloud Infrastructure

CI/CD

Agile

SDLC

Attention to Detail

Education

Bachelor's degree in computer science or related technical field

Tools

SQL Server

HDFS

ElasticSearch

IBM Infosphere

Kafka

RabbitMQ

Data Robot

Google Cloud Platform

AWS

Azure

Python

Spark

PySpark

Job description

• Build data strategy for broad or complex requirements with insightful and forward-looking approaches that go beyond the direct team and solve large open-ended problems.


• Participate in the strategic development of methods, techniques, and evaluation criteria for projects and programs.


• Drive all aspects of technical and data architecture, design, prototyping and implementation in support of both product needs as well as overall technology data strategy.


• Provide leadership and technical expertise in support of building a technical plan and backlog of stories, and then follow through on execution of design and build process through to production delivery.


• Guide a broad functional area and lead efforts through the functional team members along with the team’s overall planning.


• Represent engineering in cross-functional team sessions and able to present sound and thoughtful arguments to persuade others.


• Adapts to the situation and can draw from a range of strategies to influence people in a way that results in agreement or behavior change.


• Collaborate and partner with product managers, designers, and other engineering groups to conceptualize and build new features and create product descriptions.


• Actively own features or systems and define their long‑term health, while also improving the health of surrounding systems.


• Assist Support and Operations teams in identifying and quickly resolving production issues.


• Develop and implement tests for ensuring the quality, performance, and scalability of our application.


• Actively seek out ways to improve engineering and data standards, tooling, and processes.


• Supporting the company’s commitment to risk management and protecting the integrity and confidentiality of systems and data.

Requirements

• Education and/or experience typically obtained through a Bachelor’s degree in computer science or related technical field.


• Eight or more years of relevant related experience.


• Seven or more years of experience in the development of complex data platform, distributed systems, SaaS, cloud solutions, micro services.


• Six or more years of experience in the development of Data Warehouse, Big Data – structured & unstructured platforms, real-time & batch processing, data standards.


• Four or more years of experience in development of Business Intelligent Solutions.


• Two or more years of experience in development / operationalization of Artificial Intelligence / Machine Learning Models / Model development life cycle activities (implementing feature engineering, data pipelines, model operationalization, model monitoring).


• Demonstrated experience in delivering business‑critical systems to the market.


• Ability to influence and work in a collaborative team environment.


• Experience designing/developing scalable systems.


• Extensive experience implementing Data Warehouse (Star / Snow flake schemas) using SQL Server or equivalent, Big Data – HDFS, Elastic Search, ETL process development using IBM Infosphere or equivalent, Reusable Frameworks.


• Experience with implementing data science solutions using Python, Spark, PySpark, R, Data Robot.


• Experience with event‑driven architecture and messaging frameworks (Pub/Sub, Kafka, RabbitMQ, etc).


• Working experience with cloud infrastructure (Google Cloud Platform, AWS, Azure, etc).


• Knowledge of mature engineering practices (CI/CD, testing, secure coding, etc).


• Knowledge of Software Development Lifecycle (SDLC) best practices, software development methodologies (Agile, Scrum, LEAN etc) and DevOps practices.


• Attention to detail.


• Background and drug screen.

Core Competencies

Demonstrates expertise in developing complex data platforms and distributed systems, with a strong focus on data architecture, cloud solutions, and machine learning model operationalization. Proven ability to lead cross‑functional teams and drive technical strategies that enhance product delivery and system integrity.

Highest‑signal resume keywords

• Data Architecture


• Cloud Solutions


• Machine Learning Model Development


• Data Warehouse Implementation


• Agile Methodologies

ATS Optimization Keywords

Hard Skills

• Data Platform Development


• Big Data Processing


• SQL Server


• Python


• Spark


• ETL Process Development


• Event-Driven Architecture


• CI/CD Practices


• Software Development Lifecycle


• Business Intelligence Solutions

Soft Skills

• Collaboration


• Influencing


• Attention to Detail

Industry Keywords

• SaaS


• Microservices


• Real‑Time Processing


• Batch Processing


• Data Standards

Tools & Technologies

• Google Cloud Platform


• AWS


• Azure


• IBM Infosphere


• Kafka


• RabbitMQ


• Data Robot