Business Intelligence Engineer Data Management at J Lee Engineering

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: - Bachelors degree in Computer Science Information Systems Data Science Engineering or comparable professional experience. Masters 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: $100000 to $150000 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. Key Skills Business Intelligence,Cognos,SQL,Power BI,QlikView,Data Visualization,ssrs,Tableau,SSIS,Data Modeling,Data Warehouse,Data Analysis Skills Employment Type : Full Time Experience: years Vacancy: 1