Business Intelligence Engineer (Snowflake/AWS)

Location: Plainfield, Indiana, United States. Hybrid schedule with four days in-office and one day remote.

Salary: $101,000–$126,000 per year.

Company

hirify.global supports life science systems and technologies that enable life-changing discoveries.

What you will do

• Design, develop, and maintain ETL pipelines integrating enterprise applications, operational systems, APIs, and third-party platforms.
• Build AWS-based data lake and analytics solutions using S3, Glue, Athena, Lambda, SageMaker, and Aurora PostgreSQL.
• Design Snowflake databases, schemas, tables, views, dimensional models, semantic layers, and governed datasets.
• Develop and optimize PostgreSQL objects, data transformation logic, queries, and analytical workloads.
• Create reusable datasets, KPIs, metrics, and reporting structures for dashboards and self-service analytics.
• Prepare curated data assets for machine learning, predictive analytics, and AI initiatives while maintaining data quality and governance.

Requirements

• Bachelor’s degree in Computer Science, Information Systems, Data Analytics, Engineering, or a related field.
• 4+ years of experience in business intelligence, data engineering, analytics engineering, or a related discipline.
• Strong experience with ETL development, data integration, SQL, data modeling, and enterprise reporting datasets.
• Hands-on experience with Snowflake, PostgreSQL, and AWS cloud environments.
• Experience with PostgreSQL query optimization, schema design, indexing strategies, and performance tuning.
• This position is currently not eligible for employment sponsorship.

Nice to have

• Experience with SageMaker, AWS Glue, Athena, Lambda, S3 data lakes, or machine learning data preparation.
• Experience with Power BI, Tableau, Apache Iceberg, Parquet, or medallion architecture.
• Experience with CDC, event-driven architectures, data products, operational analytics, or advanced PostgreSQL features.
• AWS or Snowflake certifications.

Culture & Benefits

• Customer-focused culture centered on innovation, accountability, teamwork, integrity, and employee value.
• General office working conditions with a hybrid schedule.
• Work supporting life science systems and data-driven discovery.