Job description

Azenta Inc. At Azenta, new ideas, new technologies and new ways of thinking are driving our future. Our customer focused culture encourages employees to embrace innovation and challenge the status quo with novel thinking and collaborative work relationships. All we accomplish is grounded in our core values of Customer Focus, Achievement, Accountability, Teamwork, Employee Value and Integrity Job Title Business Intelligence Engineer Job Description 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.* If any applicant is unable to complete an application or respond to a job opening because of a disability, please email at Recruiting azenta.com for assistance. 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. United States Base Compensation: $101,000.00 - $126,000.00 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.

Requirements

Must-haves

All we accomplish is grounded in our core values of Customer Focus, Achievement, Accountability, Teamwork, Employee Value and Integrity
Job Title Business Intelligence Engineer
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
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
Develop and support AWS-based analytics solutions utilizing: Amazon S3
Amazon SageMaker
Amazon Athena
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

Nice-to-haves

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

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

awsaimachine learningsqlpython

Platform: workday
Effort: long