The Lead Business Intelligence Engineer will work closely with various business functions (such as HR, Finance, and others) to understand their data analytics requirements, design and develop SQL data models using DBT and Snowflake, and manage the analytics engineering technology infrastructure to securely present data to business stakeholders.
Working closely with BI Developers and Data Engineers, this role will ensure timely delivery of data models for reporting and analytics across business functions.
Key Responsibilities:
- Partner with stakeholders from HR, Finance, and other business functions to gather and analyze data requirements
- Analyze data coming from various HRMS, ERP and CRM systems (such as SAP SuccessFactors, Salesforce, etc.)
- Design and implement scalable data models with modular data solutioning approach to support consistent yet flexible reporting capabilities across the organization
- Using DBT and SQL, create and maintain robust data models to support analytics needs of multiple business teams
- Ensure data integrity and consistency while safeguarding sensitive information using effective data masking and encryption methods
- Manage and execute code deployments using version control tools, e.g., GitHub
- Collaborate with the Governance team to ensure data processes adhere to policies, procedures, and regulatory requirements
- Document technical solutions, processes, and various data artifacts
- 7+ years of experience as a Data Modeler/Database Developer/Analytics Engineer/BI Engineer
- Strong expertise in SQL programming with 5+ years of hands on experience writing complex SQL code for data analysis
- 3+ years of experience with Snowflake or similar cloud data warehouse solution such as AWS Redshift and Google BigQuery
- Strong understanding of data modeling concepts in both transactional and analytical databases
- SQL and DBT expertise, including designing and implementing scalable data models and pipelines
- Strong understanding of analytics engineering best practices, including testing, documentation, and performance optimization
- Proven expertise in implementing Data Security best practices in a Data Warehouse environment - Role Based Access Control, Data Masking, and Data Encryption
- Demonstrated proficiency in code deployment and version control using tools such as GitHub, with the ability to effectively manage code repositories, implement branching strategies, and collaborate using pull requests and code review processes
- Excellent analytical and problem-solving skills, with a commitment to high-quality analytics deliverables
- Competent verbal and written communication and presentation skills, with the ability to convey complex concepts to both technical and non-technical audiences
- Ability to work independently as well as in a team setting
- Able to work as a business partner to various functions and demonstrate ability to collaborate effectively
Beneficial technical experience:
- Experience in analyzing, manipulating, and dealing with large scale data
- Experience creating curated data models using a data mesh architecture
- Experience with HCM and ERP systems is preferred, experience with SAP SuccessFactors is a big plus
- Scripting experience in Python, JavaScript, or any other language is an advantage
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