Associate Data Engineer: Build Scalable Data Pipelines

IBM; San Diego (CA); On-site; USD 90,000 - 130,000; Full time

Job summary

IBM in San Diego invites an Associate Data Engineer to join a global team that designs, builds, and optimizes data pipelines for real-time and batch processing. You will gather and transform data, select suitable storage and processing systems, and ensure data quality for downstream analytics.

The role emphasizes collaboration with diverse engineers, consultants, and clients, using Java, Python, SQL, and Spark to turn data into actionable insights.

Qualifications

• Bachelor's degree in a related field or equivalent experience.
• Experience building data pipelines for cloud environments.
• Familiarity with SQL, Python, and data processing frameworks.
• Knowledge of ETL/ELT concepts and data warehousing.
• Willingness to travel as needed (project-based).

Responsibilities

• Design scalable data architectures and management systems for cloud environments.
• Optimize data pipelines for performance and reliability.
• Work with ETL/ELT ingestion pipelines and data integration tools.
• Collect and analyze data to provide actionable client insights.
• Create dashboards and reports to communicate findings to stakeholders.
• Ensure data quality through cleaning, validation, and preprocessing.
• Translate client requirements into solution designs and work with architects.
• Present analytical findings clearly to clients.

Skills

Java

Python

SQL

Spark

Hadoop

ETL

Data modeling

CI/CD basics

Linux

Scala

Education

Bachelor's Degree

Tools

Snowflake

BigQuery

Airflow

dbt

Spark

Hadoop

Job description

IBM in San Diego invites an Associate Data Engineer to join a global team that designs, builds, and optimizes data pipelines for real-time and batch processing. You will gather and transform data, select suitable storage and processing systems, and ensure data quality for downstream analytics.

The role emphasizes collaboration with diverse engineers, consultants, and clients, using Java, Python, SQL, and Spark to turn data into actionable insights.