Hybrid Cloud Data Engineer: ETL Pipelines & Analytics

AARATECH; Kansas City (MO); Hybrid; USD 70,000 - 80,000; Full time

Job summary

Aaratech Inc. is seeking a Data Engineer to build and maintain data pipelines on cloud platforms. You will develop ETL/ELT workflows, bring data together from multiple systems, and help keep the data that powers reporting and analytics accurate and reliable.

The role requires 2–3 years of experience, on-site or hybrid work arrangements, and US work authorization. You will write SQL and Python to transform data, collaborate with analysts, and document pipelines for reliability.

Qualifications

• Bachelor's degree in Computer Science, IT, or related field, or equivalent hands-on experience.
• 2+ years working with data — ETL development, data integration, SQL development, or database work.
• Good SQL skills with joins, aggregations, and real-world data queries.
• Experience with at least one ETL tool (Azure Data Factory, SSIS, Informatica, Talend, etc.).
• Basic familiarity with data warehouse concepts.
• Some Python scripting exposure, or a strong desire to learn it.
• Clear communicator and reliable problem-solver.

Responsibilities

• Build and maintain ETL/ELT data pipelines using Azure Data Factory, SSIS, or AWS Glue.
• Pull data from multiple sources into clean, usable datasets.
• Write SQL to transform, join, and validate data.
• Use Python scripts to automate routine data tasks.
• Monitor pipelines and troubleshoot data landing issues.
• Collaborate with analysts and business teams to deliver required data.
• Document pipelines for maintainability.

Skills

ETL development

Data integration

SQL development

Python scripting

Data modeling

Education

Bachelor's degree in CS/IT or related field

Tools

Azure Data Factory

SSIS

Informatica

Talend

dbt

Job description

Aaratech Inc. is seeking a Data Engineer to build and maintain data pipelines on cloud platforms. You will develop ETL/ELT workflows, bring data together from multiple systems, and help keep the data that powers reporting and analytics accurate and reliable.

The role requires 2–3 years of experience, on-site or hybrid work arrangements, and US work authorization. You will write SQL and Python to transform data, collaborate with analysts, and document pipelines for reliability.