Remote Data Analyst Jobs

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🔥 Senior Software Engineer (Remote - US or Canada)

Posted about 6 hours ago

📍 United States, Canada

🧭 Full-Time

💸 140000.0 - 160000.0 USD per year

🔍 Software Development

🏢 Company: Jobgether👥 11-50💰 $1,493,585 Seed about 2 years agoInternet

🔧 Requirements

5+ years of experience building scalable backend applications and APIs.
Proficiency in Go, Python, or Java, with a strong grasp of SQL and NoSQL databases (e.g., Bigtable, BigQuery, DynamoDB).
Experience working with cloud infrastructure, preferably AWS or GCP, and CI/CD pipelines.
Familiarity with containerization technologies such as Docker and Kubernetes.
Strong problem-solving and analytical skills, with the ability to communicate complex concepts clearly.

💡 Responsibilities

Design and implement ETL pipelines capable of processing large-scale datasets efficiently.
Build and maintain robust APIs for data retrieval, including support for complex query types.
Architect scalable data storage and retrieval systems using SQL/NoSQL technologies.
Transform raw data into structured, high-value data products to support business and operational decisions.
Collaborate with internal stakeholders to align data architecture with product and customer needs.
Document technical processes and mentor junior team members.
Ensure performance, security, and scalability across the data platform.

AWS Backend Development Docker Python SQL DynamoDB ETL GCP Java Kubernetes API testing Data engineering Go Nosql CI/CD RESTful APIs Data modeling Software Engineering Data analytics

Posted about 6 hours ago

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🔥 Enterprise Data Architect

Posted about 6 hours ago

📍 GBR

🧭 Full-Time

🔍 Insurance

🏢 Company: dxcjobs

🔧 Requirements

Experience in defining high quality Logical Data Models and gaining approval for such models in a complex stakeholder environment.
Experience of stakeholder management including senior stakeholders, 3rd party partners and standards organisations.
Experience of working with industry standard data models and extending those models to support business requirements.
Experience of working in an insurance business domain and with insurance logical data models, including commercial insurance.
Experience with a wide variety of technical domains from green field microservice architectures to workflow management systems, integration tooling and mainframe.
Experience of Logical Physical data mapping and of large-scale transformation projects moving from complex legacy system domains to modern digital applications.
Experience of defining transition plans and road maps for data migration, including both bulk and gradual migration.
Experience of defining patterns for and implementing BI/MI, analytics, and machine learning on large-volume datasets.
Experience of data designing and implementing data security policies and regulatory compliance.
Experience of defining and implementing governance processes for data management.
Experience of working with external standards organisations.
Experience of working with TOGAF framework.

💡 Responsibilities

Define and manage an Enterprise Data Strategy, supporting the business strategy and objectives.
Conduct detailed analysis of business processes, requirements, and scenarios to produce high quality Logical Data Models and work with senior stakeholders, third party partners, and standards organisations to gain approval for finished artefacts.
Work with and customise Industry Standard Logical Data Models to produce and maintain models tailored to the specific business domain.
Define, document and maintain business value chain for enterprise data.
Analyse business processes to identify and document key data dependency through key end-to-end business process flows.
Work with internal and external development teams and technical architects to drive logical service architecture design, external API contract design, and internal physical data model design.
Work with Technical BA's to analyse existing system behaviour, data models and business process implementations to facilitate logical to physical data mapping into existing systems to drive system integration designs and data transformation.
Design data models and patterns for downstream data exposure to facilitate accessibility for and analytics, BI, MI and reporting, both internal and external.
Work with external 3rd party standards bodies to define and maintain global messaging standards.
Based on business process analysis, understand and document life cycles of key data entities and define non-functional requirements for data consistency, integrity, availability, latency, and auditability.
Work with Security Architects to define and agree on data security classifications for data defined in data models.
Define and manage data governance framework for the program and work with existing architecture team to hand into BAU.

SQL Business Intelligence Cloud Computing Data Mining ETL API testing Data engineering REST API Microservices Data visualization Stakeholder management Data modeling Data analytics Data management

Posted about 6 hours ago

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🔥 Data Scientist – NLP & Real World Evidence (RWE) - Remote

Posted about 7 hours ago

📍 United States, Canada

🔍 Healthcare

🏢 Company: Veradigm👥 5001-10000💰 $100,000,000 Post-IPO Equity almost 10 years agoInformation Services Electronic Health Record (EHR)Hospital Information Technology Health Care

🔧 Requirements

Master’s degree in Data Science, Computer Science, Biomedical Informatics, or a related field.
Proficiency in Python and SQL.
Experience developing ML models, particularly with NLP techniques and libraries (spaCy, Scikit-learn, etc.).
Experience with Azure OpenAI or other large language models.
Familiarity with EMR systems, healthcare data standards (e.g. ICD-10, SNOMED).
Exposure to cloud environments and big data tools (e.g., Snowflake, Azure, Spark).
Demonstrated ability to work with clinical text and health data (e.g., EMRs).

💡 Responsibilities

Design, develop, and deploy NLP and ML models using Python to extract insights from unstructured and semi-structured clinical text.
Leverage Azure OpenAI and other LLM frameworks to enhance clinical data structuring and semantic understanding.
Partner closely with clinical subject matter experts to validate models, ensuring high precision and accuracy in clinical contexts.
Iterate on model development using feedback from real-world applications and clinician review.
Collaborate with Operations teams to design, implement, and optimize an end-to-end data science pipeline from R&D to production.
Ensure data integrity, reproducibility, and compliance with healthcare regulations and best practices.
Work with clients and stakeholders to identify key business problems and expected outcomes.
Explore and assess internal and external data sources to extract relevant features and patterns.
Communicate findings, methodologies, and actionable insights to both technical and non-technical audiences.

Python SQL Cloud Computing Data Analysis ETL Machine Learning Algorithms Azure Data science Data Structures CI/CD RESTful APIs Data visualization

Posted about 7 hours ago

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🔥 Senior Business Analyst

Posted about 7 hours ago

📍 Colombia

🏢 Company: GoDaddy👥 5001-10000💰 $800,000,000 Post-IPO Equity over 3 years ago🫂 Last layoff over 1 year agoWeb Hosting Domain Registrar Web Development Online Portals

🔧 Requirements

5+ years in a technical role in a corporate setting.
Proficiency in SQL for data discovery, aggregation, and extraction; experience with large datasets and AWS/Redshift preferred.
Expertise with data visualization and business intelligence tools such as Tableau or Google Analytics.
Strong communication skills to clearly explain complex analyses and support conclusions with effective visualizations.
Ability to collaborate across teams in various time zones, navigating both technical and business discussions.

💡 Responsibilities

Develop analytical project requirements and provide insights to support GoDaddy's business objectives and growth strategies.
Conduct in-depth data analysis to identify actionable insights and effectively communicate findings to influence business decisions.
Build and maintain dynamic dashboards and visualizations using advanced business intelligence tools to aid in understanding business drivers.
Design and implement end-to-end data solutions, including enterprise-wide views, dashboards, and custom reporting.
Perform large-scale data analysis and develop models for segmentation, classification, and customer behavior analysis.

AWS SQL Business Intelligence Data Analysis ETL Google Analytics Tableau Communication Skills Analytical Skills Data visualization Data modeling Data analytics

Posted about 7 hours ago

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🔥 Operations Engineer

Posted about 8 hours ago

📍 United States

🧭 Full-Time

🔍 Software Development

🏢 Company: Arrived👥 1-50

🔧 Requirements

Software engineering background with strong programming skills in Python, SQL, and modern development practices
Experience building and maintaining production data systems, APIs, or backend services
Hands-on experience with data pipeline tools (dbt, Fivetran, or similar)
Strong SQL skills and experience with data warehouses (Snowflake)

💡 Responsibilities

Build production data systems – design and implement scalable data pipelines, ETL processes, and APIs that handle structured and unstructured data from multiple sources
Develop internal applications – write maintainable code for internal tools, automation services, and integrations
Own system architecture – make technical decisions about data flow, system design, and technology stack choices that balance immediate needs with long-term scalability

AWS Backend Development Project Management Python SQL ETL Snowflake Algorithms API testing Data engineering Data Structures REST API Communication Skills CI/CD RESTful APIs DevOps Data visualization Data modeling Software Engineering Data analytics Data management

Posted about 8 hours ago

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🔥 Manager, Analytics

Posted about 8 hours ago

📍 Australia

🔍 Software Development

🏢 Company: Avetta, LLC

🔧 Requirements

Deep expertise in SQL, including writing complex queries and performance tuning.
Extensive hands-on experience with multiple reporting and BI tools such as Jasper Server, MicroStrategy, Sisense, SQL Server Reporting Services (SSRS), Power BI etc .
Extensive hands-on experience with multiple database platforms such as MySQL, Postgresql, Snowflake.
3+ years in a BI/Analytics management or senior/lead BI developer role within a software development company.
Experience architecting and supporting distributed BI systems/cloud analytics solutions.
Strong understanding of data warehousing principles, data modeling (star/snowflake schemas), and data governance.
Proven success managing multiple projects with Agile methodologies, especially involving large data sets and complex reporting requirements.
Excellent interpersonal and communication skills, with a demonstrated ability to translate technical work into business value for non-technical audiences.

💡 Responsibilities

Lead, mentor, and develop a team of BI and analytics professionals, including guidance on best practices for data modeling, ETL, and reporting.
Collaborate with product managers, business units, and stakeholders to gather and clarify BI requirements and to translate them into scalable technical solutions.
Architect, enhance, and support data warehouses and analytic data marts, primarily utilizing Jasper Server, Power BI and Snowflake.
Oversee the design, implementation, and optimization of ETL processes to ensure the accuracy and timeliness of data integrations from multiple sources.
Ensure projects are tracked in JIRA, with thorough code reviews, data quality checks, and UAT/testing prior to deployment.
Facilitate Agile ceremonies, including sprint planning, daily stand-ups, and retrospectives for the BI and Analytics team.
Drive continuous improvement in BI processes, adoption of new tools/technologies, and foster a culture of data quality and governance.
Troubleshoot and resolve data issues, working with engineering and business teams as needed to remove blockers.
Ensure smooth collaboration with engineering, infrastructure, and business analysts to provide actionable BI solutions across teams.

Leadership PostgreSQL SQL Agile Business Intelligence ETL MySQL Snowflake Communication Skills Problem Solving Data visualization Data modeling Data analytics

Posted about 8 hours ago

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🔥 Senior Analytics Engineer

Posted about 8 hours ago

📍 United States

🧭 Full-Time

💸 150000.0 - 200000.0 USD per year

🔍 Energy

🏢 Company: Arcadia👥 501-1000💰 $125,000,000 over 2 years agoDatabase CleanTech Renewable Energy Clean Energy Software

🔧 Requirements

4+ years as an Analytics Engineer or equivalent role; experience with dbt is strongly preferred
6+ years, cumulatively, in the data space (data engineering, data science, analytics, or similar)
Expert-level understanding of conceptual data modeling and data mart design
An understanding of data structures and/or database design plus deep experience with SQL and Python
Experience building data pipelines and database management including Snowflake or similar
Ability to bring a customer-oriented and empathetic approach to understanding how data is used to drive the business
Experience in technical leadership or mentorship
Strong communication and collaboration skills
Proven ability to solve complex problems in a dynamic and evolving environment

💡 Responsibilities

Transform, test, deploy, and document data to deliver clean and trustworthy data for analysis to end-users
Collaborate with subject matter experts, engineers, and product managers to identify the most elegant and effective data structures to understand our constantly growing and evolving business
Help bring engineering best practices (reliability, modularity, test coverage, documentation) to our DAG and to our Data team generally
Collaborate with data engineers to build robust, tested, scalable ELT pipelines.
Data modeling: model raw data into clean, tested, and reusable datasets to represent our key business data concepts. Define the rules and requirements for the formats and attributes of data
Data transformation: build our data lakehouse by transforming raw data into meaningful, useful data elements through joining, filtering, and aggregating source dataData documentation: create and maintain data documentation including data definitions and understandable data descriptions to enable broad-scale understanding of the use of data
Employ software engineering best practices to write code and coach analysts and data scientists to do the same

AWS Python SQL Data Analysis ETL Git Snowflake Data engineering Data Structures Communication Skills Analytical Skills Collaboration Data visualization Data modeling Data management

Posted about 8 hours ago

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🔥 Senior Solutions Engineer, West Coast

Posted about 9 hours ago

📍 United States, Canada

🧭 Full-Time

💸 118300.0 - 147800.0 USD per year

🔍 Software Development

🏢 Company: Twilio👥 5001-10000💰 $378,215,525 Post-IPO Equity almost 4 years ago🫂 Last layoff over 1 year agoMessaging SMS Mobile Apps Enterprise Software Software

🔧 Requirements

3+ years of success in a solutions engineering (presales) role with 6+ years of progressive professional experience supporting technical products.
Experience with Data Engineering, Cloud Data Warehouses, Data Modeling, and APIs
Experience with marketing technology such as marketing automation, personalization, journey orchestration, or advertising.

💡 Responsibilities

Partner with Account Executives to execute pre-sales activities including opportunity qualification, discovery, demonstrations, Proof-of-Concept, RFP responses,and justifying business value.
Become an expert builder and evangelist of Segment’s products and partner ecosystem.
Lead technical evaluations with our prospects to uncover their goals and technical pain, in order to design, demonstrate and present innovative solutions that unlock business-level gains.
Develop subject matter expertise on Customer Data Platforms (CDPs) and Segment’s role within the customer data ecosystem.
Act as a trusted advisor to consult with customers and prospects in order to influence their customer data strategy and architecture design.
Build a perspective on customer and market trends by listening to prospects and advocating for customer interests to influence Segment’s strategy and vision.

AWS Cloud Computing ETL Data engineering Data science Communication Skills Problem Solving RESTful APIs Sales experience Marketing Data modeling Scripting Data analytics Data management Customer Success

Posted about 9 hours ago

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🔥 Data Platform Engineer

Posted about 10 hours ago

📍 United States

🧭 Full-Time

💸 180000.0 - 220000.0 USD per year

🔍 Software Development

🏢 Company: Prepared👥 51-100💰 $27,000,000 Series B 8 months agoEnterprise Software Public Safety

🔧 Requirements

5+ years of experience in data engineering, software engineering with a data focus, data science, or a related role
Knowledge of designing data pipelines from a variety of source (e.g. streaming, flat files, APIs)
Proficiency in SQL and experience with relational databases (e.g., PostgreSQL)
Experience with real-time data processing frameworks (e.g., Apache Kafka, Spark Streaming, Flink, Pulsar, Redpanda)
Strong programming skills in common data-focused languages (e.g., Python, Scala)
Experience with data pipeline and workflow management tools (e.g., Apache Airflow, Prefect, Temporal)
Familiarity with AWS-based data solutions
Strong understanding of data warehousing concepts and technologies (Snowflake)
Experience documenting data dependency maps and data lineage
Strong communication and collaboration skills
Ability to work independently and take initiative
Proficiency in containerization and orchestration tools (e.g., Docker, Kubernetes)

💡 Responsibilities

Design, implement, and maintain scalable data pipelines and infrastructure
Collaborate with software engineers, product managers, customer success managers, and others across the business to understand data requirements
Optimize and manage our data storage solutions
Ensure data quality, reliability, and security across the data lifecycle
Develop and maintain ETL processes and frameworks
Work with stakeholders to define data availability SLAs
Create and manage data models to support business intelligence and analytics

AWS Docker PostgreSQL Python SQL Apache Airflow ETL Kubernetes Snowflake Apache Kafka Data engineering Spark Scala Data modeling

Posted about 10 hours ago

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🔥 Senior Data Engineer

Posted about 10 hours ago

📍 United States

🧭 Full-Time

💸 145000.0 - 200000.0 USD per year

🔍 Daily Fantasy Sports

🏢 Company: PrizePicks👥 101-250💰 Corporate about 2 years agoGaming Fantasy Sports Sports

🔧 Requirements

5+ years of experience in a data Engineering, or data-oriented software engineering role creating and pushing end-to-end data engineering pipelines.
2+ years of experience acting as technical lead and providing mentorship and feedback to junior engineers.
Extensive experience building and optimizing cloud-based data streaming pipelines and infrastructure.
Extensive experience exposing real-time predictive model outputs to production-grade systems leveraging large-scale distributed data processing and model training.
Experience in most of the following: SQL/NoSQL databases/warehouses: Postgres, BigQuery, BigTable, Materialize, AlloyDB, etc Replication/ELT services: Data Stream, Hevo, etc. Data Transformation services: Spark, Dataproc, etc Scripting languages: SQL, Python, Go. Cloud platform services in GCP and analogous systems: Cloud Storage, Cloud Compute Engine, Cloud Functions, Kubernetes Engine etc. Data Processing and Messaging Systems: Kafka, Pulsar, Flink Code version control: Git Data pipeline and workflow tools: Argo, Airflow, Cloud Composer. Monitoring and Observability platforms: Prometheus, Grafana, ELK stack, Datadog Infrastructure as Code platforms: Terraform, Google Cloud Deployment Manager. Other platform tools such as Redis, FastAPI, and Streamlit.

💡 Responsibilities

Enhance the capabilities of our existing Core Data platforms and develop new integrations with both internal and external APIs within the Data organization.
Work closely with DevOps, architects, and engineers to ensure the success of the Core Data platform.
Collaborate with Analytics Engineers to enhance data transformation processes, streamline CI/CD pipelines, and optimize team collaboration workflows.
Architect and implement Infrastructure as Code (IaC) solutions to automate and streamline the deployment and management of data infrastructure.
Develop and manage CI/CD pipelines to automate and streamline the deployment of data solutions.
Ensure code is thoroughly tested, effectively integrated, and efficiently deployed, in alignment with industry best practices for version control, automation, and quality assurance.
Serve as a Data Engineering thought leader within the broader PrizePicks technology organization by staying current with emerging technologies, implementing innovative solutions, and sharing knowledge and best practices with junior team members and collaborators.
Provide on-call support as part of a shared rotation between the Data and Analytics Engineering teams to maintain system reliability and respond to critical issues.

Leadership PostgreSQL Python SQL Apache Airflow Bash Cloud Computing ETL GCP Git Kafka Kubernetes Data engineering Data science REST API CI/CD RESTful APIs Mentoring Terraform Data modeling

Posted about 10 hours ago

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Remote Data Analyst Jobs

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Data Analyst Responsibilities

Analysts help businesses make smart decisions based on data. Their responsibilities include:

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