Engineers, Software Full Stack

T-Mobile•Bethesda, MD

1d•$150,000 - $155,000•Hybrid

About The Position

Engineers, Software Full Stack located in Bethesda, MD will work with a team of other software engineers to implement and deploy complete, cloud native systems which meet customer's requirements. Position duties and responsibilities include, but are not limited to: Build the Enterprise Data Warehouse and ETL pipelines to be used by various analytics teams. Understand various business functions and how this is reflected in data. Present analytics and data to other teams, advocating for high quality of data pipelines and data handling. Modify databases, perform tests, and solve database usage issues and malfunctions, turning raw structured and unstructured data into dimensional models that are usable by the business. Collaborate closely with developers to improve applications, interactions, and visual design, and establish best practices. Monitor the performance of APIs and optimize the response time by utilizing database techniques for faster retrieval of data. Automate steps of the data pipeline by performing manipulation and transformation while ensuring the integrity and quality of data in relational/NoSQL databases. Own the design, development, and maintenance of ongoing metrics, reports, analyses, and interactive dashboards, using business intelligence software to analyze trends, identify KPIs, and communicate key concepts to executives to drive business decisions. Integrate third-party software to the existing tech stack using APIs or SDKs to automate different processes for operational efficiency. Research and understand technology implications, perform industry benchmarking and computer analysis, and articulate solutions to adopt best engineering practices in the Data world. Document data models, data use cases, and steps of the pipeline to scale data knowledge across the organization. Telecommuting is permitted, but applicant must work from the worksite location at least 3-4 days per week. No additional national or international travel is anticipated.

Requirements

Python scripting for data transformation and integration according to business workflows, including developing and maintaining scripts to ingest, cleanse and reconcile data from thirdparty ad servers, CRM systems and backend databases, and leveraging AWS Transfer Family for secure file exchange across organizations.
Scheduling and managing ETL workflows using shell scripts and Docker-based Apache Airflow ensuring reliable execution, monitoring performance metrics, diagnosing dependency issues and optimizing job runtimes.
Utilizing AWS S3 for staging, Snowflake for data warehousing and PostgreSQL for operational storage conducting query performance optimization, enforcing data-governance standards and troubleshooting data-integrity issues across structured and semi-structured sources.
Designing, developing and maintaining Tableau dashboards to visualize ad impressions, business KPIs and other key metrics delivering stakeholder-ready reports on Tableau server.
Utilizing SQL to write, optimize and refactor complex queries in Snowflake and PostgreSQL enhancing report generation, tuning performance and performing root-cause analysis of query bottlenecks.
Leveraging AWS Secrets Manager to securely store and manage sensitive credentials and API keys and utilizing various AWS services to enhance data processing and integration workflows.

Responsibilities

Build the Enterprise Data Warehouse and ETL pipelines to be used by various analytics teams.
Understand various business functions and how this is reflected in data.
Present analytics and data to other teams, advocating for high quality of data pipelines and data handling.
Modify databases, perform tests, and solve database usage issues and malfunctions, turning raw structured and unstructured data into dimensional models that are usable by the business.
Collaborate closely with developers to improve applications, interactions, and visual design, and establish best practices.
Monitor the performance of APIs and optimize the response time by utilizing database techniques for faster retrieval of data.
Automate steps of the data pipeline by performing manipulation and transformation while ensuring the integrity and quality of data in relational/NoSQL databases.
Own the design, development, and maintenance of ongoing metrics, reports, analyses, and interactive dashboards, using business intelligence software to analyze trends, identify KPIs, and communicate key concepts to executives to drive business decisions.
Integrate third-party software to the existing tech stack using APIs or SDKs to automate different processes for operational efficiency.
Research and understand technology implications, perform industry benchmarking and computer analysis, and articulate solutions to adopt best engineering practices in the Data world.
Document data models, data use cases, and steps of the pipeline to scale data knowledge across the organization.