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Top Analytics Engineer Jobs in NYC, NY
As an Analytics Engineer, you will implement and improve analytics infrastructure, build data pipelines, develop reporting and dashboards, and work closely with product and engineering teams. You'll ensure timely delivery of high-quality solutions, using tools like dbt and SQL, and collaborate with stakeholders to meet their needs.
As a Data Analytics Engineer, you will design and implement features and services for Electronic Trading. Your responsibilities include building data pipelines to manage large datasets for client analytics and regulatory reporting, mentoring teammates, and evolving technical standards within a collaborative team.
The Senior Data Engineer is responsible for building and optimizing data pipelines, defining reusable datasets, creating a data validation framework, and ensuring user privacy. This role requires expertise in data engineering principles and experience with modern data technologies.
The Principal Analytics Engineer will oversee the development of critical data infrastructure, drive technical leadership across teams, and create sustainable value from data. Responsibilities include defining data strategy, leading complex projects, mentoring engineers, and collaborating with engineering for data quality improvements.
The Senior Analytics Engineer at Current will build data models and transformations within the data warehouse, collaborate with data teams for reporting and analytics needs, and ensure data quality. They will also design data ingestion processes and work with various teams to support analytics initiatives.
The Senior Analytics Engineer will develop data marts, ensuring data quality and integrity. They will collaborate with various teams to enhance data accessibility and will create impactful reports and dashboards for stakeholders.
As a Senior Data Engineer, you will develop and maintain foundational data models like star and snowflake schemas to support analytics and business intelligence needs. You will create and optimize key datasets, enforce dimensional modeling best practices, and collaborate with various teams to enhance insights from data. Your role will also involve optimizing data storage and ensuring efficient processing of large datasets using modern frameworks.
The Senior Recruiting Data Visualization Analyst at Dropbox will lead the development of Tableau dashboards for HR and Recruiting metrics, partner with stakeholders, analyze data for trends, enhance self-service dashboards, and conduct data literacy training. This role requires strong analytical and communication skills to support data-driven HR strategies.
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As a Senior Data Engineer II at Upside, you will lead the development of consumer marketing and app feature attribution products, collaborate with cross-functional teams including founders and data scientists, and focus on data engineering and platform development. You will also be involved in implementing marketing attribution models and work with various consumer technologies.
As a Staff Engineer on the Data & Analytics team, you will lead high-visibility projects, provide technical leadership, mentor engineers, and drive architectural decisions for the platform. You will collaborate with product teams to enhance data management ecosystems and ensure system reliability and scalability for data ingestion and processing.
The Lead Analytics Engineer at Dashlane will design and implement reliable data models, collaborate with business and technical teams, maintain data quality, and provide training on data visualization tools. The role involves creating scalable database designs and optimizing data workflows within a hybrid work environment.
As a Senior Data Engineer, you will design and improve data infrastructure, build data pipelines for various stakeholders, and collaborate closely with Data Science and Analytics teams to produce valuable business insights and support core products.
The role involves leading data engineering initiatives, designing robust data infrastructure, developing data pipelines, and mentoring team members. It requires collaboration with stakeholders to create effective data solutions and ensuring compliance with data governance policies.
Design, build, and optimize scalable data systems; collaborate with cross-functional teams; manage data pipelines; improve data governance; enhance tools and processes for data workflows. Focus on developing frameworks that enhance data quality and reliability to improve healthcare experiences.
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