Remote Data Science Jobs

Data engineering

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🔥 Director of Data & Insights Product

Posted about 1 hour ago

📍 United States

🧭 Full-Time

💸 138000.0 - 150000.0 USD per year

🔍 Education

🏢 Company: Gradient Learning

🔧 Requirements

5+ years of experience working in the K-12 space
3+ years of experience in data product development
3+ years of experience translating complex data into educator-friendly visualizations using Tableau
3+ years of people management experience
3+ years of experience with Snowflake or comparable cloud-based data warehousing platforms (strongly preferred)
Experience using AI or machine learning to enhance data analysis or deliver scalable, educator-facing insights (strongly preferred)
Familiarity with LTI standards, LMS platforms, and education data interoperability; direct experience with Canvas LMS (strongly preferred)
Knowledge of data privacy, security, and protection standards, particularly as they relate to PII and educational data (FERPA, COPPA, etc.) (preferred)

💡 Responsibilities

Design, Refine, and Lead the Data & Insights Product Strategy
Oversee Data & Insights Product Development and Delivery
Strengthen Data Infrastructure in Partnership with Information Systems
Lead the Data & Insights Product Delivery Team

SQL Data Analysis ETL Machine Learning People Management Product Management Snowflake User Experience Design Cross-functional Team Leadership Tableau Product Development Data engineering Communication Skills Agile methodologies RESTful APIs Data visualization Stakeholder management Strategic thinking Data modeling Data analytics Data management

Posted about 1 hour ago

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🔥 Senior Security Engineer (SIEM/Cribl) - Northeast region (Remote)

Posted about 2 hours ago

📍 United States

🧭 Full-Time

🔍 Information Security

🔧 Requirements

5+ years of experience in security engineering, with a primary focus on SIEM platforms.
Hands-on experience with at least two of the following SIEM platforms: Splunk, Microsoft Sentinel, Elastic, Google SecOps, CrowdStrike NG-SIEM, LogScale
2+ years of experience with Cribl or similar observability pipeline tools (e.g., Logstash, Fluentd, Kafka).
Strong knowledge of log formats, data normalization, and event correlation.
Familiarity with detection engineering, threat modeling, and MITRE ATT&CK framework.
Proficiency with scripting (e.g., Python, PowerShell, Bash) and regular expressions.
Deep understanding of logging from cloud (AWS, Azure, GCP) and on-prem environments.

💡 Responsibilities

Architect, implement, and maintain SIEM solutions with a focus on modern platforms
Design and manage log ingestion pipelines using tools such as Cribl Stream, Edge, or Search (or similar).
Optimize data routing, enrichment, and filtering to improve SIEM efficiency and cost control.
Collaborate with cybersecurity, DevOps, and cloud infrastructure teams to integrate log sources and telemetry data.
Develop custom parsers, dashboards, correlation rules, and alerting logic for security analytics and threat detection.
Maintain and enhance system reliability, scalability, and performance of logging infrastructure.
Provide expertise and guidance on log normalization, storage strategy, and data retention policies.
Lead incident response investigations and assist with root cause analysis leveraging SIEM insights.
Mentor junior engineers and contribute to strategic security monitoring initiatives.

AWS Python Bash Cloud Computing GCP Kafka Kubernetes API testing Azure Data engineering CI/CD RESTful APIs Linux DevOps JSON Ansible Scripting

Posted about 2 hours ago

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🔥 Lead Machine Learning Infrastructure Engineer - Infrastructure & Data

Posted about 4 hours ago

📍 United States

🧭 Full-Time

💸 185500.0 - 293750.0 USD per year

🔍 Software Development

🔧 Requirements

Strong technical expertise in designing and building scalable ML infrastructure.
Experience with distributed systems and cloud-based ML platforms.
Proficiency in programming languages such as Python, Java, or Scala.
Deep understanding of ML workflows, including data pipelines, model training, and deployment.
Passion for innovation and eagerness to implement the latest advancements in ML infrastructure.
Strong problem-solving skills and ability to optimize complex systems for performance and reliability.
Collaborative mindset with excellent communication skills to work across teams.
Ability to thrive in a fast-paced, dynamic environment with evolving technical challenges.

💡 Responsibilities

Design, implement, and optimize distributed systems and infrastructure components to support large-scale machine learning workflows, including data ingestion, feature engineering, model training, and serving.
Develop and maintain frameworks, libraries, and tools that streamline the end-to-end machine learning lifecycle, from data preparation and experimentation to model deployment and monitoring.
Architect and implement highly available, fault-tolerant, and secure systems that meet the performance and scalability requirements of production machine learning workloads.
Collaborate with machine learning researchers and data scientists to understand their requirements and translate them into scalable and efficient software solutions.
Stay current with advancements in machine learning infrastructure, distributed computing, and cloud technologies, integrating them into our platform to drive innovation.
Mentor junior engineers, conduct code reviews, and uphold engineering best practices to ensure the delivery of high-quality software solutions.

AWS Docker Python Cloud Computing Kubernetes Machine Learning Algorithms Data engineering Data science CI/CD RESTful APIs Scala Software Engineering

Posted about 4 hours ago

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🔥 Data Analyst - Finance

Posted about 4 hours ago

📍 USA

🧭 Full-Time

🔍 Fintech

🏢 Company: Comun

🔧 Requirements

Expert-level SQL knowledge with demonstrated ability to optimize complex queries (non-negotiable)
At least 3+ years of practical experience in data engineering or analytics roles with financial data
3+ years of experience at a fintech or financial services industries in the payments or lending space at a similar role
Solid understanding of finance concepts and principles
Proven track record building data pipelines and ETL processes
Experience implementing cost modeling and optimization analytics
Problem-solving mindset with strong analytical skills
Excellent communication skills to explain complex technical and financial concepts

💡 Responsibilities

Design and implement scalable data pipelines to establish and maintain a solid fund flow process
Automate financial reconciliation processes and generate actionable reports
Develop and maintain revenue and cost models to identify growth opportunities and provide insights for strategic decision-making
Build analytical tools to identify and quantify cost optimization opportunities across the organization
Monitor vendor performance metrics and evaluate new vendor opportunities
Implement data solutions to detect financial anomalies and uncover efficiency opportunities that drive business value
Perform cohort-level performance analysis to develop a deeper understanding on customer unit economics
Collaborate with finance, data, growth, product, and engineering teams to develop robust financial data architecture
Contribute to our mission of financial inclusion by enabling data-informed product and pricing decisions

AWS PostgreSQL Python SQL Data Analysis ETL Snowflake Data engineering FastAPI Financial analysis Data modeling Finance

Posted about 4 hours ago

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🔥 Data Engineer (Contract)

Posted about 6 hours ago

📍 LatAm

🧭 Contract

🏢 Company: AbleRental Property Management Real Estate

🔧 Requirements

10+ years of data engineering experience with enterprise-scale systems
Expertise in Apache Spark and Delta Lake, including ACID transactions, time travel, Z-ordering, and compaction
Deep knowledge of Databricks (Jobs, Clusters, Workspaces, Delta Live Tables, Unity Catalog)
Experience building scalable ETL/ELT pipelines using tools like Airflow, Glue, Dataflow, or ADF
Advanced SQL for data modeling and transformation
Strong programming skills in Python (or Scala)
Hands-on experience with data formats such as Parquet, Avro, and JSON
Familiarity with schema evolution, versioning, and backfilling strategies
Working knowledge of at least one major cloud platform: AWS (S3, Athena, Redshift, Glue Catalog, Step Functions), GCP (BigQuery, Cloud Storage, Dataflow, Pub/Sub), or Azure (Synapse, Data Factory, Azure Databricks)
Experience designing data architectures with real-time or streaming data (Kafka, Kinesis)
Consulting or client-facing experience with strong communication and leadership skills
Experience with data mesh architectures and domain-driven data design
Knowledge of metadata management, data cataloging, and lineage tracking tools

💡 Responsibilities

Shape large-scale data architecture vision and roadmap across client engagements
Establish governance, security frameworks, and regulatory compliance standards
Lead strategy around platform selection, integration, and scaling
Guide organizations in adopting data lakehouse and federated data models
Lead technical discovery sessions to understand client needs
Translate complex architectures into clear, actionable value for stakeholders
Build trusted advisor relationships and guide strategic decisions
Align architecture recommendations with business growth and goals
Design and implement modern data lakehouse architectures with Delta Lake and Databricks
Build and manage ETL/ELT pipelines at scale using Spark (PySpark preferred)
Leverage Delta Live Tables, Unity Catalog, and schema evolution features
Optimize storage and queries on cloud object storage (e.g., AWS S3, Azure Data Lake)
Integrate with cloud-native services like AWS Glue, GCP Dataflow, and Azure Synapse Analytics
Implement data quality monitoring, lineage tracking, and schema versioning
Build scalable pipelines with tools like Apache Airflow, Step Functions, and Cloud Composer
Develop cost-optimized, scalable, and compliant data solutions
Design POCs and pilots to validate technical approaches
Translate business requirements into production-ready data systems
Define and track success metrics for platform and pipeline initiatives

AWS Python SQL Cloud Computing ETL GCP Kafka Airflow Azure Data engineering Scala Data modeling

Posted about 6 hours ago

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🔥 Forward Deployed Engineer - Architect

Posted about 6 hours ago

📍 USA

🔍 SaaS

🏢 Company: DevRev👥 251-500💰 $100,825,173 Series A 10 months agoDeveloper Platform Customer Service CRM Artificial Intelligence (AI)Developer APIs Software

🔧 Requirements

3+ years in software development, AI/ML engineering, or technical consulting.
Strong proficiency in Python and/or Golang.
Familiarity with large language models (LLMs), prompt engineering, and frameworks like RAG and function calling.
Hands-on experience with AWS, GCP, or Azure, and modern DevOps practices (CI/CD, containers, observability).

💡 Responsibilities

Design & Deploy AI Agents
Integrate Systems
Optimize Performance
Own Requirements
Prototype & Iterate
Lead Execution
Advise Customers

AWS Docker Python Software Development Cloud Computing Data Analysis GCP Kubernetes Machine Learning Algorithms API testing Azure Data engineering Communication Skills CI/CD Customer service RESTful APIs DevOps SaaS

Posted about 6 hours ago

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🔥 Data Engineer (m/f/d)

Posted about 6 hours ago

📍 Germany

🧭 Full-Time

🏢 Company: Roadsurfer👥 501-1000💰 $5,330,478 almost 4 years agoLeisure Rental Tourism Recreational Vehicles

🔧 Requirements

Experience with Segment, Braze, or similar CDP/CEP platforms
Basic knowledge of data transformation tools
Familiarity with data governance practices, such as data ownership, naming conventions, and data lineage
Experience implementing data privacy measures such as consent tracking and anonymization
Familiarity with data quality metrics and monitoring techniques
Understanding of data privacy regulations (GDPR, CCPA)
Good communication skills, with the ability to work with cross-functional teams and stakeholders

💡 Responsibilities

Ensure reliability through automated tests, versioned models, and data lineage
Assist in implementing data governance policies to ensure data consistency, quality, and integrity across the CDP and CEP platforms
Support the automation of data validation and quality checks, including schema validation and data integrity monitoring
Help define and track data quality metrics and provide regular insights on data cleanliness and health
Assist in ensuring compliance with data privacy regulations (e.g., GDPR, CCPA), including implementing consent tracking and anonymization measures
Work with cross-functional teams to standardize data definitions, naming conventions, and ownership practices
Help maintain data cleanliness through automated data cleanup processes and identify areas for improvement
Support the analytics team by ensuring data is structured correctly for reporting and analysis

SQL Apache Airflow ETL Data engineering Postgres RESTful APIs Compliance JSON Data visualization Data modeling Data analytics Data management

Posted about 6 hours ago

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🔥 Grupo QuintoAndar | Tech Lead Manager (AI Core Platform)

Posted about 15 hours ago

📍 Brazil

🧭 Full-Time

🔍 Software Development

🏢 Company: Grupo QuintoAndar

🔧 Requirements

Solid understanding of the engineering challenges of deploying machine learning systems to production;
Solid understanding of systems, software and data engineering best practices;
Proficiency with cloud-based services;
Proficiency in Python or another major programming language;
Have experience building backend systems, event driven architectures and rest/http applications
Have experience building solutions with LLMs (RAG, fine-tuning);
Have experience building AI agents and AI powered applications, familiarity with agentic frameworks (LangGraph, LangChain, AutoGen, CrewAI);
Experience leading teams and managing careers.

💡 Responsibilities

Lead a small team of Data Scientists and Machine Learning Engineers to build solutions based on AI/ML.
Be a technical reference to the team, including doing hands-on engineering work.
Shaping the technical direction of our products, translating business requirements into solutions.
Discuss business requirements with the Product Manager and other stakeholders.

AWS Backend Development Docker Leadership Project Management Python Software Development SQL Artificial Intelligence Cloud Computing Kubernetes Machine Learning Software Architecture Algorithms Data engineering Data science Data Structures REST API Communication Skills CI/CD Agile methodologies RESTful APIs Excellent communication skills Problem-solving skills Team management Technical support Data modeling

Posted about 15 hours ago

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🔥 Engineering Manager (Data)

Posted about 17 hours ago

📍 Romania

🧭 Full-Time

🔍 Software Development

🏢 Company: Plain Concepts👥 251-500 Consulting Apps Mobile Apps Information Technology Mobile

🔧 Requirements

At least 3 years of experience as a Delivery Manager, Engineering Manager, or similar role in software, data-intensive or analytics projects.
Proven experience managing client relationships and navigating stakeholder expectations.
Strong technical background in Data Engineering (e.g., Python, Spark, SQL) and Cloud Data Platforms (e.g., Azure Data Services, AWS, or similar).
Solid understanding of scalable software and data architectures, CI/CD practices for data pipelines, and cloud-native data solutions.
Experience with data pipelines, sensor integration, edge computing, or real-time analytics is a big plus.
Ability to read, write, and discuss technical documentation with confidence.
Strong analytical and consultative skills to identify impactful opportunities.
Agile mindset, always focused on delivering real value fast.
Conflict resolution skills and a proactive approach to identifying and mitigating risks.

💡 Responsibilities

Understanding the business and technical objectives of data-driven projects.
Leading multidisciplinary teams to deliver scalable and robust software and data solutions on time and within budget.
Maintaining proactive and transparent communication with clients, helping them understand the impact of data products.
Supporting the team during key client interactions and solution presentations.
Designing scalable architectures for data ingestion, processing, and analytics.
Collaborating with data engineers, analysts, and data scientists to align solutions with client needs.
Ensuring the quality and scalability of data solutions and deliverables across cloud environments.
Analyzing system performance and recommending improvements using data-driven insights.
Providing hands-on technical guidance and mentorship to your team and clients when needed

AWS Python SQL Agile Cloud Computing Azure Data engineering Spark Communication Skills CI/CD Client relationship management Team management Stakeholder management Data analytics

Posted about 17 hours ago

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🔥 Senior Software Engineer (Remote - US or Canada)

Posted about 17 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 17 hours ago

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