About the job Business Intelligence Engineer Data Management
Job summary :
We are in search of a pragmatic, detail-focused Business Intelligence Engineer Data Management to oversee data architecture, pipelines, and governance that facilitate analytics and decision-making throughout the organization. You will develop and maintain cloud data warehouses, ETL / ELT procedures, data models, and catalogs; enhance data quality and performance; and collaborate closely with analysts, product teams, and engineers to provide accurate and timely business insights. This position is exclusively available to candidates residing in the United States. U.S. work authorization is mandatory; we do not provide visa sponsorship.
Principal duties :
- Design, construct, and sustain resilient ETL / ELT pipelines and data integration workflows (both batch and streaming) within the enterprise data warehouse.
- Create and sustain dimensional and normalized data models that facilitate analytics, reporting, and self-service business intelligence.
- Construct and enhance SQL queries, materialized views, and data marts for optimal performance and cost-effectiveness.
- Establish and uphold standards for data governance, lineage, metadata management, and data cataloging.
- Establish and oversee data quality measures; assess and resolve data discrepancies.
- Establish and uphold access controls, data classification, and compliance-related measures (knowledge of GDPR / CCPA).
- Collaborate with business intelligence and reporting teams to develop reusable semantic layers and dashboards using Tableau, Power BI, or Looker.
- Collaborate with product, engineering, finance, and operations stakeholders to convert business requirements into analytical solutions and key performance indicators (KPIs).
Produce comprehensive documentation, data dictionaries, and onboarding resources for data users.
Guide junior engineers and enhance best practices, continuous integration / continuous deployment, and testing for analytics code and pipelines.Required skills :
Proficient in SQL with expertise in query optimization and performance enhancement.Practical experience with a minimum of one cloud data warehouse (Snowflake, BigQuery, Amazon Redshift).Proficient in constructing ETL / ELT pipelines utilizing tools such as dbt, Airflow, Fivetran, Matillion, Talend, or bespoke Python / Scala implementations.Proficient in BI / reporting tools such as Tableau, Power BI, Looker, or equivalent.Comprehensive knowledge of data modeling methodologies (star / snowflake schemas, OLAP versus OLTP).Proficient in data governance, data cataloging (e.g., Alation, Collibra, DataHub), and data quality tools.Proficient in programming or scripting with Python or an alternative language for data processing and automation.Proficient in problem-solving, communication, and stakeholder management.Proficiency in cloud platforms (AWS, GCP, or Azure) and infrastructure-as-code is advantageous.Academic background and professional experience :
Bachelor's degree in Computer Science, Information Systems, Data Science, Engineering, or comparable professional experience. Master's degree is preferable but not mandatory.2 to 7 years of experience in business intelligence, data engineering, or data management roles (advanced positions may necessitate over 7 years).Demonstrated history of implementing production analytics systems and collaborating across functions with business stakeholders.Annual compensation :
Base salary range : $100,000 to $150,000 per annum, contingent upon experience, role level, and U.S. location. The precise offer will depend on qualifications and changes for market and area.
Location : Remote / U.S. based (must be located in the United States)
Compensation and benefits :
Competitive base salary with the potential for an annual performance-based bonus.Equity or stock options, if applicable.Extensive medical, dental, and vision insurance (employer-supported).401(k) retirement plan featuring employer contribution matching.Ample paid time off (vacation, sick leave, business holidays) and parental leave.Policy for remote work and adaptable scheduling.Stipend for professional growth and budget for training (conferences, seminars, certifications).Stipend for home office equipment and reimbursement for technology expenses.Short-term and long-term disability insurance, life insurance, and commuter benefits (where applicable).Employee Assistance Program (EAP) and wellness resources.Equitable access :
We are an employer that provides equal opportunities. We appreciate diversity and are dedicated to fostering an inclusive atmosphere for all employees.