Entry-Level Data Engineer: Analytics & Cloud Pipelines

IBM; Durham (NC); On-site; USD 71,000 - 107,000; Full time

Job summary

IBM Consulting is hiring an Associate Data Engineer to harness data, design scalable architectures, and build pipelines for batch and real-time processing. You will work across teams to select data management systems and identify data requirements for insightful analysis, tackling integration challenges and ensuring data quality.

Responsibilities include designing scalable data architectures, enhancing ETL/ELT pipelines, data collection and analysis, and creating dashboards to communicate

Qualifications

• Ability to incorporate a variety of statistical and machine learning techniques.
• Basic understanding of Cloud (AWS, Azure, etc).
• Ability to use programming languages like Java, Python, Scala to build pipelines to extract and transform data from a repository to a data consumer.
• Ability to use ETL tools and/or data integration tools to prepare and transform data as needed.
• Proficiency with Linux, SQL, Python, Spark, Hadoop and Java.
• Exposure to ETL/ELT projects and data warehouse design.

Responsibilities

• Assist in designing and implementing scalable data architecture for modern cloud environments.
• Optimize existing data pipelines and processes for performance.
• Work with ETL/ELT ingestion pipelines.
• Collect and analyze data to identify trends and provide actionable insights.
• Troubleshoot data-related issues and resolve data inconsistencies.
• Create visualizations, dashboards, and reports for stakeholders.

Skills

Java

Python

SQL

ETL

Data modeling

Agile

Education

High School Diploma/GED

Bachelor's Degree

Tools

dbt

Snowflake

BigQuery

Airflow

Job description

IBM Consulting is hiring an Associate Data Engineer to harness data, design scalable architectures, and build pipelines for batch and real-time processing. You will work across teams to select data management systems and identify data requirements for insightful analysis, tackling integration challenges and ensuring data quality.

Responsibilities include designing scalable data architectures, enhancing ETL/ELT pipelines, data collection and analysis, and creating dashboards to communicate