Company Description
Since opening our first self-storage facility in 1972, Public Storage has grown to become the largest owner and operator of self-storage facilities in the world. With thousands of locations across the U.S. and Europe, and more than 170 million net rentable square feet of real estate, we're also one of the largest landlords.
We've been recognized as A Great Place to Work by the Great Place to Work Institute. And, our employees have also voted us as having Best Career Growth , ranked us in the Top 5% for Work Culture , and in the Top 10% for Diversity and Inclusion .
We're a member of the S&P 500 and FT Global 500. Our common and preferred stocks trade on the New York Stock Exchange.
Workplace

• One of our values pillars is to work as OneTeam and we believe that there is no replacement for in-person collaboration but understand the value of some flexibility. Public Storage teammates are expected to work in the office five days each week with the option to take up to three flexible remote days per month.
• Our office is based in Plano, east of Interstate 75 near E. Park Blvd, just North of Historic Downtown Plano.

Job Description
As a key member of our leading-edge, full-stack team, the Data Engineer II role offers an unparalleled opportunity to advance your career in a stable, S&P 500 company renowned for its innovative spirit, collaborative team culture and commitment to technical excellence. In this elevated position, you are instrumental in advancing our cutting-edge data infrastructure; optimizing data flow and storage, and spearheading data science and data engineering initiatives that drive our company's growth this year and for many years after. This role is best suited for those who thrive in a culture of mentoring, performance, accountability, and technical leadership, offering a prime environment to refine various skills @ data engineering, machine learning operations, and learn/apply advanced leadership skills.
Responsibilities:
Advanced Collaboration: Define and lead projects in collaboration with Data Scientists and Engineers to enhance data workflows, implementing cutting-edge solutions to meet complex data challenges.
Applied System Architecture Development: Take charge of designing and executing significant enhancements to our data systems to support advanced analytical capabilities and meet evolving business needs.
Pipeline Management: Architect, build, and manage sophisticated data pipelines from a variety of sources, ensuring scalability and reliability.
Data Governance: Spearhead the development and enforcement of data management practices, ensuring the highest quality of data in our data lake and compliance with data privacy standards.
ML Ops Leadership: Play a critical role in the strategy and execution of Machine Learning Operations, driving the adoption of best practices and innovative solutions.
Code Excellence: Set the standard for code maintainability, performance, and best practices, mentoring junior engineers and leading by example.
Strategic Documentation: Create, maintain, and evolve detailed documentation of data architectures, systems, and processes, facilitating knowledge sharing and operational efficiency.
Qualifications
Required Qualifications:
A BS in computer science 5 years of experience OR a Master's degree in Computer Science with 3 years relevant experience as a Data Engineer.
Must possess have multiple years of experience of hands on technical programming skills in SQL and Python.
Possess exceptional communication skills - written and verbal.
3-5 years of experience in developing and deploying production-grade code in cloud environments, with a proven track record in engineering best practices applied to machine learning.
Advanced proficiency in relational database modeling, Data Mart design, SQL development, and performance tuning. Must be expert at SQL coding and troubleshooting.
Experience (4 years) with Python/SQL for sophisticated data processing and API development.
Experience (3-5 years) in managing analytical data warehouses and advanced columnar data stores, with a strong preference for experience in Big Query.
Demonstrable skills, including advanced query optimization, version control systems, code review processes, and comprehensive documentation.
Proven track record (2 years) in designing, implementing, and maintaining scalable ETL data architectures using advanced tools like Airflow, DBT, Luigi, or Azkaban.
Desired Qualifications:
Solid experience (2 years) with advanced Data and ML Orchestration, Containerization, and GPU Compute technologies such as Docker, Kubernetes, Spark, or Dask.
Experience (2 years) in a senior DevOps or MLOps role, leading the development of machine learning infrastructure with tools like Terraform or Google Cloud Deployment Manager/GKE.
Proficiency (2 years) with advanced dashboarding tools, with a preference for Looker ML.
Experience (2 years) in developing and deploying complex ML solutions in public cloud environments like Google Cloud Platform, AWS, or Azure.
This role represents a significant step forward for those eager to influence the future of data engineering, offering a dynamic, supportive environment where innovation and collaboration are not just valued but essential to our success. If you are passionate about pushing the boundaries of data engineering and ready to take on this challenging yet rewarding role, we invite you to apply.
Additional Information
All your information will be kept confidential according to EEO guidelines. REF1766R