Data Analytics and Integration Specialist chez Beam Therapeutics
Beam Therapeutics · Cambridge, États-Unis d'Amérique · On-site
- Bureau à Cambridge
Company Overview:
Beam Therapeutics is a biotechnology company committed to establishing the leading, fully integrated platform for precision genetic medicines. To achieve this vision, Beam has assembled a platform with integrated gene editing, delivery and internal manufacturing capabilities. Beam’s suite of gene editing technologies is anchored by base editing, a proprietary technology that is designed to enable precise, predictable and efficient single base changes, at targeted genomic sequences, without making double-stranded breaks in the DNA. This has the potential to enable a wide range of therapeutic editing strategies that Beam is using to advance a diversified portfolio of base editing programs. Beam is a values-driven organization committed to its people, cutting-edge science, and a vision of providing life-long cures to patients suffering from serious diseases.
Position Overview:
Beam is looking for a highly energetic Data Analytics and Integration Specialist to join our growing IT team. The Data Analytics and Integration Specialist will be responsible for designing, building, and maintaining integration solutions using Boomi AtomSphere platform. The role ensures seamless data flow between cloud and on-premise systems, supporting enterprise applications and business processes. The candidate will be heavily involved in data migration and integration efforts, particularly using Boomi, SAP, LabVantage LIMS, MES systems and Amazon Redshift Data Warehousing.
Responsibilities:
- ETL Development & Data Integration - Design and implement robust ETL (Extract, Transform, Load) processes to integrate data from diverse sources while ensuring data quality and Strong experience in Boomi development to create, test, and deploy integrations, including data capture, data mapping, transformations, testing and validation.
- AWS & Cloud Data Management - Manage and optimize AWS-based data pipelines, specifically handling data movement from S3 buckets to Leverage AWS services such as S3, IAM, Lambda, Glue, and others for seamless data processing and storage.
- Data Modeling and Design - Develop efficient data models and database schemas within Amazon Redshift, considering data redundancy, normalization, and performance optimization.
- Data Security and Governance - Implement data security measures within Redshift, ensuring compliance with data privacy regulations and access control policies.
- Documentation & Reporting - Develop technical documentation for data warehouse architecture, data models, ETL processes, and key performance indicators (KPIs).
Qualifications:
- Bachelor’s degree in Computer Science, Information Systems, or a related field.
- 12+ years of relevant experience.
- Experience with other ETL Tools.
- Experience with data visualization tools (e.g., Tableau, Power BI).
- Familiarity with data security and privacy best practices.
- Boomi Integration Development: Hands-on experience developing integrations using Boomi, including data mapping, transformations, testing, and validation.
- SQL Proficiency: Extensive experience writing complex SQL queries for data manipulation, aggregation, and analysis within relational databases.
- Amazon Redshift Expertise: Strong understanding of Redshift architecture, data loading mechanisms, and query optimization techniques for managing large-scale data warehouses.
- AWS & Cloud Data Warehousing: Experience migrating and managing data from S3 buckets to Redshift and working with other AWS services (S3, Lambda, Glue, IAM).
- Data Migration & ETL Experience: experience migrating data from SAP to LabVantage LIMS and MES to SAP and Boomi highly preferred.
- Onsite requirements: Candidates are expected to come onsite 2 days per week and as needed to complete job duties.
The salary range below reflects the full-time base salary range we expect to pay for this role at the time of posting. Base pay will be determined based on several factors including, but not limited to, relevant experience, education, scope of job, internal comparisons, and market data.
