Data Engineer
fracto solutionsLouisville (KY)
About the role
Key Responsibilities:
Build and maintain data pipelines (ETL/ELT) to ingest data from multiple sourcesDevelop and optimize SQL queries for analytics and reporting use casesAssist in managing and scaling data warehouses and data lakesPerform data validation, cleansing, and quality monitoringCollaborate with Data Analysts, Data Scientists, and Product teamsSupport cloud-based data solutions on AWS, GCP, or AzureDocument data models, pipelines, and technical workflowsTroubleshoot and resolve pipeline failures or data discrepanciesFollow best practices related to data security, governance, and complianceRequired QualificationsMaster’s degree (required) in Data Science, Computer Science, Information Systems, Engineering, Analytics, or a related fieldStrong proficiency in SQL (joins, window functions, aggregations) Working knowledge of Python for data processing and automationUnderstanding of data modeling, ETL concepts, and database designFamiliarity with relational databases such as PostgreSQL, MySQL, SQL Server, or OracleExposure to at least one cloud platform (AWS, GCP, or Azure) Knowledge of Git or other version control systemsStrong analytical thinking and problem-solving skillsExcellent written and verbal communication skills
Before you apply
Applying takes about a minute. These four things decide how fast it moves after that.
Your profile is current
It's what we read first. Occupations, seniority and locations matter more than a long history.
Two examples you can talk through
Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.
A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
Employers plan around it, and it's the question that stalls offers most often.
Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.
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