Business Intelligence Engineer

How Youll Add Value:

The Business Intelligence (BI) Engineer is responsible for designing developing and maintaining enterprise data and analytics solutions that enable data-driven decision-making across the organization. This role will build and optimize cloud-based data platforms design scalable ETL (Extract Transform Load) pipelines and develop curated datasets that support reporting dashboards advanced analytics and Artificial Intelligence initiatives.

Working within AWS Snowflake and PostgreSQL-based data environments the BI Engineer will transform complex business and operational data into trusted actionable insights while ensuring data quality governance and scalability.

What Youll Do:

Data Engineering and ETL Development:

• Design develop and maintain ETL pipelines that integrate data from enterprise applications operational systems APIs and third-party platforms
• Build automated processes to extract load and transform structured and unstructured data into analytics-ready datasets
• Implement data validation cleansing enrichment and monitoring processes
• Optimize data pipelines for performance scalability and reliability

Snowflake Data Platform:

• Design and manage Snowflake databases schemas tables views and data models
• Develop and maintain dimensional operational and semantic data models to support analytics and reporting. Create structured and governed datasets that enable self-service business intelligence
• Optimize Snowflake performance through effective clustering partitioning and query tuning

AWS Data Lake & Cloud Analytics:

• Develop and support AWS-based analytics solutions utilizing:
  • Amazon S3
  • Amazon SageMaker
  • AWS Glue
  • Amazon Athena
  • AWS Lambda
  • Amazon Aurora PostgreSQL
• Design and maintain S3 data lake structures and table architectures that support enterprise reporting and analytics
• Support data ingestion and transformation processes from multiple internal and external data sources
• Design develop and optimize PostgreSQL database objects including schemas tables views materialized views stored procedures and data transformation logic to support analytics and reporting workloads

Reporting & Business Intelligence:

• Partner with business stakeholders to understand reporting and analytics requirements
• Create and maintain reusable datasets KPIs metrics and reporting structures
• Support dashboard and visualization development utilizing BI and reporting tools
• Enable self-service analytics through governed data models and semantic layers

AI & Advanced Analytics Enablement:

• Collaborate with Data Science and AI teams to prepare and curate datasets for machine learning models
• Support data engineering activities required for Amazon SageMaker and AI initiatives
• Develop scalable data assets that support predictive analytics and operational intelligence

Data Governance & Quality:

• Establish and maintain data quality standards and controls
• Document data lineage mappings business rules and transformation logic
• Ensure compliance with data governance security and regulatory requirements
• Participate in master data and metadata management initiatives

What You Will Bring:

• 
  
• Bachelors degree in Computer Science Information Systems Data Analytics Engineering or related field
• 4 years of experience in Business Intelligence Data Engineering Analytics Engineering or related disciplines
• Strong experience with ETL development and data integration.
• Hands-on experience with Snowflake
• Hands-on experience with PostgreSQL including query optimization schema design indexing strategies and performance tuning
• Strong SQL development data modeling and PostgreSQL database development expertise
• Experience working within AWS cloud environments
• Experience developing and managing enterprise reporting datasets
• Knowledge of dimensional modeling data warehousing and analytics best practices
• Experience with Python or other scripting languages for data processing

Preferred Qualifications:

• Experience with Amazon SageMaker and machine learning data preparation

• Experience with AWS Glue Athena Lambda and S3-based data lake architectures

• Experience with Power BI Tableau or similar analytics platforms

• Familiarity with Apache Iceberg Parquet or modern data lake table formats

• AWS and/or Snowflake certifications

• Experience supporting AI predictive analytics or enterprise data strategy initiatives

• Experience with PostgreSQL advanced features such as partitioning materialized views JSON/JSONB extensions and analytical query optimization

• Experience implementing medallion architecture (Bronze/Silver/Gold) or similar multi-layer data lake design patterns

• Experience with Change Data Capture (CDC) event-driven architectures data products and operational analytics platforms

Your Working Conditions:

• General office setting
• This position qualifies for a hybrid schedule - 4 days in-office1 day working remote

Join us and help enable lifechanging discoveries by keeping critical life science systems running reliablyevery day.

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*This position is currently not eligible for any employment sponsorship.*

Azenta is an Equal Opportunity Employer. This company considers candidates regardless of race color age religion gender sexual orientation gender identity national origin disability or veteran status.

The posted pay range for this position is an estimate based on current market data and internal pay structure. Final compensation may vary above or below this range depending on factors such as experience education (including licensure and certifications) qualifications performance and geographic location among other relevant business or organizational needs.