Top Business Intelligence Engineer Jobs in San Francisco
As a Senior Business Intelligence Engineer at Cash App, you will create and optimize data models, standardize business metrics, build data pipelines, and create dashboards to help teams make informed decisions. You will work with a highly data-driven team to analyze large datasets and advance Cash App's vision of economic empowerment through data-driven products.
The Senior BI Engineer will be responsible for designing and building scalable BI platforms and customizable business-ready datasets. They will empower teams to make data-driven decisions and improve products and services. The engineer should have a deep understanding of big data and experience in creating semantic layers and self-service BI analytics.
Design and develop data models in Snowflake with DBT for internal business partners. Write advanced SQL queries for ELT and data warehousing. Collaborate with teams to drive projects and promote self-service reporting. Ensure data governance, security, and privacy best practices are followed. Experience with GitHub, SQL, Python, and Power BI.
Designs, develops, and programs methods and systems to analyze big data sources and generate insights and solutions. Interacts with teams to identify data analysis questions and issues. Cleanses and integrates large datasets from multiple sources. Identifies meaningful insights and communicates findings to managers.
As a Senior Analytics Engineer at Calm, you will lead the development of scalable data models for both internal and external data products. You will collaborate with various teams to design and build data models, inform key decision makers through data insights, and drive strategic decisions through data-driven analysis. Your role will involve developing, testing, and documenting core data models to support business success.
Develop data models, write SQL queries and Python code, identify data integrity issues, enforce data policies, build and scale data models, implement database structures, and maintain documentation.
Lead the creation and execution of a comprehensive data strategy, guide the technical vision for developing a reliable data platform and infrastructure, oversee data functions, deliver actionable insights, and recruit a world-class data team.
Design, develop, and maintain scalable solutions for metrics, reports, and analyses to meet business needs. Collaborate with teams to measure customer experience and drive business outcomes. Troubleshoot data quality issues and recommend improvements to data sources. Have 5+ years of experience in the data/BI space and proficiency in SQL and data visualization tools like Tableau.
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Design fundamental processes and data pipelines, develop insights through analytics, work with product and engineering teams, design experiments, and develop models to automate decisions in support of safety goals.
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Seeking a Senior Data Scientist to drive actionable insights and analytics capabilities for cloud operations products. Must have experience in applied statistics, fluency in operations products, and the ability to work with cross-functional teams.
As a Tech Lead for Data at Forge, you will bring your substantial experience in data solutions to help unlock the power of our data for our customers. You will handle the increasing complexity and demand for data from various sources, enabling customers to make informed investment decisions. You will lead the data engineering team in designing and implementing a cutting-edge data platform and pipelines along with direct collaboration with crucial teams such as Product, Research, and Engineering enhance the data platform.
Build large, scalable platforms using cutting edge data technologies, define data assets, own data architecture, improve data quality, collaborate with cross-functional teams, design and launch data models, solve data integration problems, implement security model, participate in on-call rotations
Design, implement, and scale data products to support data processing and analytical needs. Transform raw data into actionable insights, collaborate with cross-functional teams, and ensure data accuracy and availability.
As a Senior Data Engineer at Calm, you will work with various data sources to help stakeholders create products and answer business questions. Responsibilities include working with business stakeholders, standardizing data approaches, evangelizing data-driven decision making, ensuring data quality, collaborating on data models, and mentoring data engineers. Past projects include setting up reporting systems, creating user-level feature stores, remodeling critical data pipelines, and integrating data warehouse with third-party applications. Ideal candidates have proficiency in SQL, experience with data pipelines and modeling, and the ability to translate business requirements into technical solutions.
Senior Data Scientist responsible for analyzing large datasets using SQL and scripting languages to derive actionable insights for improving customer experience. Collaborate with cross-functional teams to drive meaningful change and implement A/B experiments. Design and analyze metrics, build data visualizations, and communicate findings effectively.
Seeking a Data Analytics leader with 10+ years of experience in BI & Data, with a focus on managing high-performing teams and driving strategic decision-making through data analysis and insights. Must have expertise in SQL, Python, and R, and experience scaling and developing data science teams.
The Lead Data Specialist will supervise a team within Data Management, manage day-to-day operations, and interact with internal study teams and external end users to maintain exceptional database integrity.
In this role, you will lead our data engineering efforts and coordinate the collection, filtering, and preprocessing of data. You will be responsible for the quality and quantity of data used to train our systems. You should be passionate about data and have excellent software engineering skills. Communication and familiarity with python are also important.
Develop standardized data models to access and process real-world data for generating regulatory-grade evidence in support of cancer detection. Collaborate with cross-functional teams and external collaborators to ensure data quality and develop data processing strategies. Apply statistical methods and machine learning algorithms for data analysis and interpretation.
Serve as a Data Scientist on the Sales Analytics team at Pinterest, using data to drive efficiency and revenue growth. Analyze complex data sets, develop forecasting models, and provide actionable insights to influence decisions. Must have 3+ years of experience in data analysis, strong SQL knowledge, programming skills in Python, and expertise in data visualization tools like Tableau.
The Data Analytics Senior Associate at Clarify will be responsible for interpreting, analyzing, and mapping healthcare data, developing data analysis using SQL and statistical programming languages, shaping customer reports, building relationships with customers, and serving as a data expert within the organization.
Seeking a Sr Data Scientist, Business Analytics at Slickdeals to analyze large datasets, surface actionable insights, conduct A/B experiments, and drive data-informed business strategy. Must have 5+ years of experience in statistics or data science with advanced proficiency in Excel, SQL, and data visualization tools.
Develop scalable data pipelines, work with Data Engineering teams, gather customer requirements, and contribute to team culture.
Join Gantri as a Senior Data Engineer to design and implement scalable data pipelines, build data warehousing solutions, and enable advanced analytics capabilities. Collaborate with teams to integrate data collection, create data models, and implement data governance best practices. Conduct exploratory data analysis and provide insights for strategic decision-making.
Design, implement, and maintain data engineering tools, workflows, and platforms for a clean energy startup. Architect, mentor, and support data ingestion platform for cross-company use. Improve data quality and build analytical tools to automate data pipelines.
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