Business Intelligence Engineer

How You’ll 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 You’ll 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:

• Bachelor's 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-office,1 day working remote

Join us and help enable life‑changing discoveries by keeping critical life science systems running reliably—every day.

#IND123

*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.