Senior Data Engineer — Cloud Data Pipelines & ETL

RadioJobs

San Antonio, Northern (TX, KY)

Hybrid

USD 120,000 - 160,000

Full time

3 days ago

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Benefits offered by this job

Medical, dental & vision

Paid vacation

401K plan

Employee Assistance Program

Volunteer & Spirit days

Job summary

iHeartMedia is seeking a senior data engineer in San Antonio to design, build, and maintain data pipelines and analytics solutions. You will work with data scientists, analysts, and product teams to translate requirements into reliable, scalable data products.

The role emphasizes performance, data quality, and end-to-end data workflows in a fast-paced environment. Expertise in Python (PySpark, Pandas) and SQL is essential, along with hands-on AWS experience (Glue, CodePipeline, ECS).

Qualifications

6+ years of professional experience in data engineering.
Experience developing high-performance applications for large enterprises.
Hands-on AWS cloud experience including Glue, CodePipeline, and ECS.
Strong proficiency in Python (including PySpark, Pandas, and DataFrames) and SQL.
Experience designing, developing, and maintaining data pipelines using AWS Glue or similar technologies.
Experience building and managing ETL/ELT workflows using Airflow, AWS Step Functions, or similar tools.
Understanding of data engineering concepts including ingestion, transformation, validation, storage, and pipeline monitoring.
Familiarity with data quality, pipeline monitoring, troubleshooting, and performance optimization.
Database experience with Postgres, MongoDB, DynamoDB, and Athena.
Experience with Git and collaborative software development practices.
Experience with agile development methodologies.
Proven track record of meeting project timelines with a sense of urgency.

Responsibilities

Develop, test, deploy, and maintain data solutions that support business requirements, web applications, models, and analytics.
Collaborate with data scientists, analysts, product teams, and stakeholders to understand requirements and deliver reliable data solutions.
Design, build, and maintain data pipelines and ETL/ELT workflows using PySpark, AWS Glue, Pandas, and orchestration tools like Airflow or AWS Step Functions.
Implement data ingestion, transformation, validation, storage, and pipeline monitoring.
Build infrastructure to support model training, scoring, and retraining, along with reporting.
Deploy and manage applications and pipelines using AWS CodePipeline and ECS.
Monitor data quality, troubleshoot issues, and optimize pipeline performance.
Collaborate with a small, agile team.
Resolve technical issues through debugging and troubleshooting.