Senior Data Production Engineer

T-Mobile•Philadelphia, PA

8d•$105,100 - $189,600•Onsite

About The Position

At T-Mobile Advertising Solutions (T-Ads), we're building privacy-first advertising and data products powered by advanced machine learning, large-scale data processing, and cloud technologies. Our proprietary algorithms enable rich consumer insights, intelligent audience solutions, and measurable performance for advertisers while maintaining a strong commitment to consumer privacy. We are adding a creative and motivated Senior Data Engineer to join our team, where you’ll use modern technologies in big data, cloud, and metadata. As a tech-first product company, the work you do will have a direct impact on our customers and the business. You'll work closely with other engineers, data scientists, and product managers, gaining a holistic understanding of how our systems come together. We adhere to structured design principles inspired by Lean Development, and we encourage continuous learning and growth. As part of our team, you'll enjoy mentoring, brainstorming, and pairing up to tackle ambitious challenges. Our supportive culture fosters a collaborative atmosphere where everyone can thrive.

Requirements

Bachelor's Degree plus 5 years of related work experience OR Advanced degree with 3 years of related experience (Required)
Acceptable areas of study include Computer Engineering, Computer Science, a related subject area (Required)
4-7 years Hands-on implementation and architectural familiarity with streaming data, relational and non-relational databases, and distributed processing technologies. (Required)
4-7 years Designing and developing advanced data engineering tasks in Python, SQL, Spark, and related Python libraries (e.g., pandas, scikit-learn, scipy, numpy). (Required)
4-7 years Advanced knowledge in building complex data pipelines and cloud bases services (GCP) to support robust and scalable infrastructure (Airflow, Kafka). (Required)
Strong background in software engineering, large-scale data and algorithms, cloud architecture, and design thinking. (Required)
At least 18 years of age
Legally authorized to work in the United States

Nice To Haves

Experience with production-level engineering around GIS and geospatial data processing. (Preferred)
Familiarity with DevOps practices and tools for DataOps.
Ability to work quickly and precisely, capturing requirements and designing before implementation.
Knowledge of Google BigQuery and tools for solving data-centric problems and working with graph datasets and databases.

Responsibilities

Design and develop data engineering solutions that enable data pipelines, visualization, and analytical tools to support business requirements.
Innovate, implement, support, and iterate on scalable big data pipelines and ETL processes.
Write robust, efficient, and highly maintainable code in Python, Spark and Scala.
Contribute to team knowledge sharing and drive the advancement of new data engineering capabilities.
Assist technical, product, and operational leaders in project definition, including estimating, planning, and scoping work to meet objectives.
Also responsible for other duties/projects as assigned by business management as needed