Data Analyst: ETL Automation & AI-Powered Insights

Altair Data Resources, Inc.

Brentwood (TN)

On-site

USD 60,000 - 90,000

Full time

10 days ago

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Job summary

Altair Data Resources, Inc. is seeking a Data Analyst with experience in data processing, analysis, and automation in a collaborative, high-growth environment. The role emphasizes Python, SQL, and ETL workflows to process, validate, analyze, and deliver data.

AI-assisted tools will be used to boost productivity and automate routine tasks. You will develop and maintain data pipelines, troubleshoot data issues, monitor quality, and support reporting with Tableau/Power BI.

Qualifications

Two years of professional experience in data analysis, data processing, ETL development, or related role.
Practical experience using Python for data cleaning, transformation, and automation; pandas preferred.
Strong knowledge of SQL, including joins, filters, aggregations, and multi-table queries.
Experience developing or maintaining ETL workflows with relational databases and data quality controls.
Troubleshooting data processing failures and data discrepancies, implementing reliable solutions.
Familiarity with Excel and reporting/visualization tools (Tableau, Power BI); Alteryx is a plus but not required.
Interest in AI-assisted tools to support coding, data analysis, and process improvement with responsible use.
Strong analytical, organizational skills and attention to detail with large datasets.
Ability to work independently and with teams; document processes and explain findings.
Bachelor’s degree in a relevant field or equivalent experience.

Responsibilities

Develop and maintain Python scripts and SQL queries to extract, transform, analyze, and deliver data.
Build, maintain, and troubleshoot ETL workflows combining data from multiple sources for analysis or client delivery.
Acquire data from primary and secondary sources and maintain databases and data processing systems.
Interpret data, analyze results using statistics, identify trends in complex datasets.
Clean, validate, and reconcile data to resolve errors and ensure accuracy.
Use AI tools to assist with coding, troubleshooting, and process improvement while validating outputs.
Document workflows, business rules, and quality control procedures.
Collaborate with management and teams to understand requirements and deliver within timelines.
Identify opportunities to automate manual processes and improve data quality.