Senior Data Engineer (Python)

Hyundai Autoever America•Irvine, CA

2d•$96,550 - $138,061•Onsite

About The Position

We are seeking a motivated and detail-oriented Senior Data Engineer to join our growing data engineering team. The ideal candidate will have strong experience in Python-based data engineering, workflow orchestration using Apache Airflow, and building scalable data solutions using Lakehouse and Medallion Architecture (Bronze, Silver, Gold) principles. In this role, you will collaborate with data scientists, analysts, architects, and business stakeholders to design, develop, and optimize modern data pipelines that support analytics, reporting, and advanced data-driven initiatives. The successful candidate will have hands-on expertise in data ingestion, transformation, data quality, automation, and cloud-based data platforms.

Requirements

7+ years of experience in data warehouse or MDM applications.
Bachelor's degree in computer science, Information Technology, or related field.
Extensive knowledge of SQL and experience with relational databases.
Strong programming and scripting skills, including Python and PL/SQL.
Hands-on experience developing ETL/ELT data pipelines and supporting production data workloads.

Nice To Haves

Experience implementing Lakehouse architectures and Bronze/Silver/Gold (Medallion) data models.
Experience with cloud-based data platforms such as Azure Data Lake, AWS, or GCP.
Familiarity with Spark/PySpark and distributed data processing frameworks.
Experience with Git, CI/CD pipelines, and DevOps practices.
Experience designing reusable frameworks for data ingestion, transformation, validation, and monitoring.
Familiarity with data governance, security, compliance, metadata management, master data management, or reference data management standards.

Responsibilities

Design, develop, and maintain scalable and reliable Python-based data pipelines for ingesting, processing, and transforming large volumes of data.
Build and manage data workflows using Apache Airflow, including scheduling, monitoring, alerting, and troubleshooting production jobs.
Implement and support Medallion Architecture (Bronze, Silver, Gold) data layers to enable efficient data processing, governance, and analytical consumption.
Develop robust ETL/ELT solutions to ingest data from databases, APIs, flat files, streaming sources, and third-party systems into enterprise data platforms.
Create reusable Python frameworks and libraries to standardize data ingestion, transformation, validation, and monitoring processes.
Apply data quality checks, validation rules, and reconciliation processes to ensure accuracy and reliability of data assets.
Optimize data pipelines for performance, scalability, fault tolerance, and cost efficiency.
Manage production data workloads, perform root cause analysis, and implement performance tuning strategies.
Design and maintain data models that align with business requirements and support analytics, reporting, and machine learning use cases.
Collaborate with cross-functional teams to translate business requirements into scalable technical solutions.
Develop automation solutions for operational processes, deployment activities, and data quality monitoring.
Implement CI/CD best practices for data engineering workflows, including version control, testing, and automated deployments.
Create and maintain monitoring dashboards, alerts, and operational metrics for data pipeline health and performance.
Ensure adherence to data governance, security, compliance, and metadata management standards.
Document data architecture, pipeline designs, transformation logic, and operational procedures.
Support the implementation of master data management, reference data management, and enterprise data integration initiatives as needed.
Contribute to the continuous improvement of data engineering best practices, coding standards, and architectural frameworks.