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Data engineering

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🔥 Data Engineer (Remote only in US)

Posted 27 minutes ago

📍 United States

💸 64000.0 - 120000.0 USD per year

🔧 Requirements

Strong PL/SQL, SQL development skills
Proficient in multiple languages used in data engineering such as Python, Java
Minimum 3-5 years of experience in Data engineering working with Oracle and MS SQL
Experience with data warehousing concepts and technologies including cloud-based services (e.g. Snowflake)
Experience with cloud platforms like Azure and knowledge of infrastructure
Experience with data orchestration tools (e.g. Azure Data Factory, DataBricks workflows)
Understanding of data privacy regulations and best practices
Experience working with remote teams
Experience working on a team with a CI/CD process
Familiarity using tools like Git, Jira
Bachelor's degree in Computer Science or Computer Engineering

💡 Responsibilities

Design, implement and maintain scalable pipelines and architecture to collect, process, and store data from various sources.
Unit test and document solutions that meet product quality standards prior to release to QA.
Identify and resolve performance bottlenecks in pipelines due to data, queries and processing workflows to ensure efficient and timely data delivery.
Implement data quality checks and validations processes to ensure accuracy, completeness and consistency of data delivery.
Work with Data Architect and implement best practices for data governance, quality and security.
Collaborate with cross-functional teams to identify and address data needs.
Ensure technology solutions support the needs of the customer and/or organization.
Define and document technical requirements.

Python SQL ETL Git Java Oracle Snowflake Azure Data engineering CI/CD RESTful APIs

Posted 27 minutes ago

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🔥 Senior Growth Engineer

Posted about 2 hours ago

📍 United States

🧭 Full-Time

💸 140000.0 - 160000.0 USD per year

🔍 Email Security

🏢 Company: Valimail

🔧 Requirements

4+ years of experience with Python, SQL, or similar languages, with hands-on experience in automation and data flow management in platforms like Snowflake, Segment, Zapier, and Planhat.
2+ years in an operations role supporting Sales, Marketing, Customer Success, or Finance, with a demonstrated ability to align data operations with strategic business goals.
Required proficiency in Snowflake, Segment (or other CDP solutions), and BI tools (e.g., Sigma, PowerBI).
Familiarity with Zapier, Planhat (or similar tools such as Gainsight or ChurnZero), Salesforce, and Atlassian are a plus.

💡 Responsibilities

Oversee and optimize data flow across core platforms, including Snowflake, Sigma, Segment, Salesforce, and Planhat, ensuring seamless integration and reliable data access for cross-functional teams.
Build strong, collaborative relationships with Marketing, Sales, Finance, Product, and Engineering, facilitating data-driven insights and project alignment across departments.
Analyze customer data to derive insights that inform strategic decision-making, delivering actionable reports that support growth objectives.
Spearhead automation and optimization projects, implementing solutions that improve data flow and system efficiency.
Lead key cross-functional initiatives, ensuring smooth execution and alignment across multiple departments.
Provide valuable insights and recommendations to leadership, aligning data-driven findings with broader business objectives.
Tackle a wide range of tasks, from technical troubleshooting to strategic planning and cross-departmental collaboration.

Project Management Python SQL Business Intelligence Data Analysis ETL Salesforce Snowflake Operations Management API testing Data engineering REST API Communication Skills Analytical Skills CI/CD Problem Solving DevOps Cross-functional collaboration Data visualization Strategic thinking Data modeling Data management

Posted about 2 hours ago

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🔥 Data & AI Engineer (Frankfurt, Germany)

Posted about 5 hours ago

📍 Germany

🔍 AI and data analytics consulting

🏢 Company: Unit8 SA

🔧 Requirements

MSc level in the field of Computer Science, Machine Learning, Applied Statistics, Mathematics, or equivalent work experience.
Proficient software engineer who has experience in applying a blend of software engineering, machine learning, and statistical methods to solve real-world business problems
Proficient in one of the following languages: Python, Scala, Java.
Experience with cloud technologies is a strong plus.

💡 Responsibilities

Work with our customers to understand their challenges, design and implement solutions.
Closely collaborate with other data scientists, software engineers and business stakeholders.
Evaluate, compare and present results to technical and non-technical audience.
Contribute to the implementation and engineering of systems at different scales: from small proof-of-concepts to larger end-to-end data systems.
Implement best practices in CI/CD

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

Posted about 5 hours ago

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🔥 Senior Software Engineer, AI

Posted about 5 hours ago

📍 United States

🧭 Full-Time

🔍 Software Development

🏢 Company: Fieldguide👥 101-250💰 $30,000,000 Series B 12 months agoArtificial Intelligence (AI)Document Management

🔧 Requirements

5+ years of engineering experience
Excitement for product-focused application of ML/AI - this will be a production-focused role
Exceptional technical proficiency with at least one programming language, particularly Python or TypeScript
Understanding of ML concepts like supervised/unsupervised/self-supervised learning, neural networks and deep learning
Understanding of modern ML/AI technologies, including natural language processing (NLP) and LLMs (e.g., GPT-3+, open source models, etc.), RAG architectures, and their applications
Experience architecting systems and data pipelines that can handle the ingestion, digitalization, storage, and retrieval of document-heavy data sets, including document processing, search, and classification
Experience in developing, testing, evaluating and deploying ML models
Ability to collaborate on all aspects of product strategy and UX
Experience shaping an early stage tech stack and product, and engineering organization

💡 Responsibilities

Be an essential technical contributor at a Series B company as it scales.
Play a leadership role on the end-to-end development of features, specifically in regards to making architectural decisions and trading off different approaches.
Bring a mindset of continuous improvement to your work. You’ll be responsible for making our technology and processes better over time.
Understand how to optimize for iteration speed while maintaining a high quality bar and technical rigor.

AWS Backend Development GraphQL PostgreSQL Python SQL Artificial Intelligence Cloud Computing Data Analysis Data Mining Full Stack Development Git Keras Machine Learning Numpy PyTorch React.js Software Architecture TypeScript Data engineering REST API Pandas React Tensorflow CI/CD DevOps NodeJS Software Engineering

Posted about 5 hours ago

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🔥 Senior Data Analyst

Posted about 7 hours ago

📍 Ireland, United States (AZ, CA, CO, CT, FL, GA, IL, IN, IA, KS, MA, MI, MN, MO, NE, NJ, NY, NC, PA, SD, TN, TX, UT, WA, WI)

🔍 Data Analysis

🏢 Company: Sojern👥 501-1000💰 $9,842,000 over 1 year ago🫂 Last layoff over 1 year agoDigital Marketing Advertising Platforms SaaS Travel

🔧 Requirements

3+ years of experience in a data-driven role, preferably in analytics, data engineering, or business intelligence.
Strong proficiency in SQL (writing complex queries, working with relational databases).
Exposure to building ETL pipelines
Familiarity with BI tools (Tableau, Power BI, Looker, etc.) and the ability to create meaningful data visualizations.
Ability to work in a fast-paced environment, manage multiple priorities, and communicate insights effectively to both technical and non-technical stakeholders.

💡 Responsibilities

Work closely with Sales, Finance, Product, and Marketing teams to understand business needs and translate them into data solutions.
Analyze large datasets to identify trends, performance metrics, and actionable insights that support strategic business initiatives.
Develop detailed reports and dashboards using Tableau to help stakeholders make data-driven decisions.
Collaborate with data scientists and operations analysts to support testing and analysis on campaigns.
Build, optimize, and maintain ETL pipelines to process and transform raw data into structured, meaningful datasets.
Work with SQL, Python, and BigQuery to extract, clean, and manipulate data from multiple sources.
Ensure data quality, integrity, and consistency across different data sources.

Python SQL Apache Airflow Business Intelligence Data Analysis ETL Jenkins Tableau Algorithms Data engineering Data Structures REST API Reporting Data entry Data visualization Data modeling Data analytics Data management

Posted about 7 hours ago

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🔥 Principal Data Engineer

Posted about 7 hours ago

📍 United Kingdom

🧭 Full-Time

🔍 Insurance

🏢 Company: external

🔧 Requirements

Extensive experience of designing and building end to end data solutions (10 years +)
Experience of carrying out data engineering design and build activities using agile working practices
Experience of Databricks solutions, Databricks administration and pyspark
Data Factory/Synapse Workspace – for building data pipelines or synapse analytics pipelines
Data Lake – Delta Lake design pattern implementation experience in Azure Data Lake Gen2
Synapse Warehouse/Analytics – Experience in Synapse data mappings, external tables, schema creation from SSMS, knowledge on how Synapse pool works behind the scenes
Azure Active Directory – for Managed identities creation and usage or for generating service principles for authentication and authorization
Version Control – Experience in building Data Ops i.e., CICD pipelines in Azure DevOps with managed identity
Unit Testing – Experience in writing unit tests for data pipelines
Data Architecture – Knowledge or experience in implementing, Kimball style Data Warehouse
Data Quality – Experience in applying Data Quality rules within Azure Data Flow Activities
Data Transformation – Extensive hands on with Azure Data Flow Activities for Cleansing, transforming, validation and quality checks
Azure Cloud – Knowledge and confidence in effective communication on Azure Cloud Subscriptions

💡 Responsibilities

Create or guide the low-level design of data solutions
Be responsible for the quality of the overall data platform(s)
Be responsible for coding standards, low level design and ingestion patterns for the data platform(s)
Develop high complexity, secure, governed, high quality, efficient data pipelines
Set the standards and ensure that data is cleansed, mapped, transformed and optimised for storage
Design and build of data observability and data quality by design into all Data pipelines
Build solutions that pipe transform data into data lake storage areas, physical database models and reporting structures across data lake, data warehouse, business intelligence systems and analytics applications
Build physical data models that are appropriately designed to meet business needs and optimise storage requirements
Carry out unit testing of own code, peer testing of others code
Ensure that effective, and appropriate documentation that brings transparency and understandability are in place for all content on the data platform(s)
Coach and mentor Senior Data Engineers, Data engineers & Associate Data Engineers
Create high complexity BI solutions

Python SQL Agile Business Intelligence ETL Microsoft Power BI Apache Kafka Azure Data engineering CI/CD Data modeling Data analytics

Posted about 7 hours ago

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🔥 Principal Engineer (Go), Analytics

Posted about 8 hours ago

📍 Worldwide

🧭 Full-Time

🔍 Software Development

🏢 Company: GitLab👥 1001-5000💰 $268,000,000 Series E over 5 years ago🫂 Last layoff about 2 years agoDeveloper Tools DevOps Open Source SaaS Cloud Security

🔧 Requirements

Significant professional experience as a Principal Engineer, or relevant hands-on management and leadership experience, across multiple development teams.
Significant professional experience with Go. Significant experience with Ruby on Rails, Postgres, ClickHouse, NATS/Kafka are also a plus.
Extensive experience building high-throughput, realtime distributed systems that perform reliably and at scale.
Expert knowledge and experience in CI/CD using DevSecOps best practices and a strong interest working across analytics and insights development.
Experience developing solutions that can scale from resource-constrained on-premise applications, to mission-critical SaaS platforms with tens of millions of users
Demonstrated capacity to clearly and concisely communicate complex problems and solutions.
Experience with performance and optimization problems and a demonstrated ability to both diagnose and prevent these problems.
Comfort working in a highly agile, intensely iterative software development process.
Experience owning a project from concept to production, including proposal, discussion, and execution.

💡 Responsibilities

Contribute to the overall direction of the Analytics stage and company-wide reporting and analytics initiatives by collaborating and making proposals across several teams on their engineering work, and helping their team members make informed decisions in alignment with strategic plans
Teach, mentor, grow, and provide advice to other domain experts and individual contributors across several teams. Advise on resourcing requirements and provide feedback on promotions into technical leadership roles
Plan improvements and features with a 12-month view and ensure that OKR-level goals are aligned across the stage
Solve technical problems of the highest scope, complexity, and ambiguity while looking for innovation opportunities between several teams and demonstrating a willingness to experiment and to boldly confront problems of large complexity and scope
Interface with Engineering Managers and Senior Management, and enable Staff Engineers to engage on stage-level aspects of larger (sub-department wide) initiatives. Provide a point of escalation for sub-department teams facing complex technical challenges
Propose initial technical implementations which support architectural changes that solve scaling and performance problems
Interact with customers and other external stakeholders as a consultant and spokesperson for the work of your sub-department
Identify slow and inefficient code across multiple products

Backend Development Leadership PostgreSQL Software Development SQL Git Kafka Kubernetes Ruby on Rails Clickhouse Data engineering Go REST API Communication Skills Analytical Skills Collaboration CI/CD DevOps Data analytics SaaS

Posted about 8 hours ago

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🔥 Staff Software Engineer (CLAW Data Pod)

Posted about 8 hours ago

📍 United States

🧭 Full-Time

🔍 Software Development

🏢 Company: NerdWallet

🔧 Requirements

8+ years in software engineering, with a strong background in backend development, distributed systems and data pipelines.
3+ years of experience with AWS, Snowflake, DBT, Airflow or any other compatible systems.
3+ years of experience building APIs and building scalable backend systems.
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field (or equivalent practical experience).
Proficiency in modern programming languages such as Java, Python or Typescript.
Experience with microservices architecture, RESTful APIs, and cloud infrastructure (AWS, GCP, or Azure).
Strong understanding of database systems (both SQL and NoSQL), with experience in high-volume data processing.
Knowledge of security best practices, particularly in financial services.
Familiarity with CI/CD pipelines, containerization, and orchestration technologies like Docker and Kubernetes.
Experience in consumer credit, lending, loans, or insurance, with a solid understanding of industry regulations, underwriting processes, and risk assessment.

💡 Responsibilities

Driving meaningful and real revenue for Nerdwallet’s CLAW division
Serving as a mentor to the engineers on the team you are assigned to
Serving as a trusted advisor and tech lead for our Engineering Managers
Delivering large amounts of features to live in a high quality fashion, serving as an example of what good looks like to the team
Helping to drive our existing culture towards better engineering practices
Helping to drive our existing culture towards strong continuous improvement thinking
Helping to drive our existing culture towards failing fast and repairing faster
Partnering with Management to continuously develop the engineering roadmap for our team

AWS Backend Development Docker Leadership Python SQL Java Kubernetes Snowflake TypeScript Airflow Data engineering Nosql Communication Skills Analytical Skills CI/CD Problem Solving Agile methodologies RESTful APIs Mentoring DevOps Microservices Teamwork Data visualization Data modeling Software Engineering Data analytics

Posted about 8 hours ago

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🔥 Sr. Principal Cyber Metrics & Reporting Engineer - Remote US

Posted about 11 hours ago

📍 United States

🔍 Life Science

🔧 Requirements

Minimum Bachelor's degree in Cybersecurity, Data analytics, Information Systems, or a related field.
A minimum of 8 years of demonstrable experience in cyber metrics and reporting, business analytics, requirements analysis, forecasting, industry research, planning, and/or management consulting required to enable data storytelling to enable visualization
Experience in SQL data modeling, SQL query development and understanding of ETL is required.
Understanding of designing and developing cybersecurity dashboards using tools like Tableau, Power BI, or similar.
Strong experience with requirements analysis and testing
Awareness of relevant industry trends and standard processes in cybersecurity metrics and reporting.
Ability to collect, analyze, and interpret large datasets to derive relevant insights and trends.
Ability to effectively collect and communicate complex information to customers.
Proactive and self-motivated approach to work, with excellent problem-solving and analytical skills.
Superb communication and storytelling skills, with the ability to shape messages for various audiences; including insights to executive-level audiences.
Analytical approach, with the ability to analyze data and identify insights.
Strong collaboration and customer management skills with a track record of successful delivery across multi-functional teams.
Ability to work effectively at all levels of the organization, from executive committee to individual employees.
Demonstrated Project Management, Scrum, Agile skills is required

💡 Responsibilities

As part of our multi-year strategy, shape, develop and implement an effective cybersecurity metrics & reporting requirements capability
Partner with customers to define report requirements, ensuring clarity and feasibility
Documents detailed reporting specifications, including data sources, metrics, and presentation format.
Validates report designs, data, and developed reports against business requirements.
Conducts detailed testing on reports, focusing on data preciseness, visual integrity, and usability.
Works with visualization and data & analytics teams to resolve any identified issues.
Conduct data discovery tied to requirements, including exploratory data analysis, data quality assessment.
Analyze requirements and data sources to identify patterns, key insights, action items, and storytelling potential.
Translate data into value while assessing effective data visualization, experience design and trending analytics linked to business and cybersecurity objectives.
Describe the key elements of a successful data story: knowing one’s audience, defining a goal, maintaining engagement, and being explicit about the takeaways.
Measure how a data story achieves its intended goals and where it can be optimized.
Identify, design and implement requirements to inform reporting, dashboards and strategy.
Identify and create metrics to measure performance through automated dashboards.

SQL Cybersecurity Data Analysis ETL Tableau Data engineering Data visualization Data modeling Data analytics

Posted about 11 hours ago

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🔥 Engineering Manager, Machine Learning

Posted about 12 hours ago

📍 United States

🧭 Full-Time

💸 185000.0 - 220000.0 USD per year

🔍 Software Development

🏢 Company: WellSaid

🔧 Requirements

5+ years of experience managing a software engineering team and a proven track record.
2+ years of experience using Cloud platforms (GCP, AWS, etc),
Background in Machine learning frameworks (such as PyTorch), and data processing tools (Spark, Pandas, etc.) are a big bonus but not mandatory.
You are proficient in software development practices, including specing, documenting, testing, reviewing, deploying, and monitoring, and are passionate about writing clean, defensible code.
Excellent communication and collaboration skills to work effectively with cross-functional teams, including software engineers, data engineers, product managers, execs, and other stakeholders.
You are flexible and capable of working with a diverse team with various communication styles and needs. You are empathic and supportive.
You create equitable processes across the entire employee lifecycle. You are particularly mindful of addressing the needs of marginalized people.
Experience in text-to-speech, speech-to-text, audio libraries, or cloud storage is a bonus.

💡 Responsibilities

Build and lead a high-performing and collaborative machine learning team, fostering an environment of innovation, growth, and accountability.
Collaborate with Product Management and other stakeholders to define, prioritize, and deliver the ML roadmap, aligning it with business goals and technical feasibility.
Ensure that complex projects are effectively scoped, planned, executed, and delivered on time while meeting cross-team quality standards.
Oversee multiple concurrent machine learning projects simultaneously, facilitating planning, and generally ensuring that deliverables are met on time.
Own and run team standups, sprint planning, and other delivery ceremonies.
Work one-on-one with team members to meet their needs, providing regular and constructive feedback. You’ll show concern and success for the well-being of others and do what you can to support people.
Conduct design, code and pull request reviews with the team.
Champion best practices in machine learning and software engineering including testing, documentation, readability, defensibility, etc.
Manage team resources effectively by prioritizing projects based on impact while balancing budget constraints for infrastructure (e.g., compute resources) or tooling needs.
Foster customer empathy within the team by introducing real-world use cases, facilitating discussions on customer pain points, reviewing feedback loops, and ensuring alignment with user needs.
All together you’ll foster an inclusive team culture and working environment.

AWS Leadership Project Management Python Software Development SQL Agile Cloud Computing Data Analysis GCP Git Machine Learning People Management Product Management PyTorch SCRUM Software Architecture Algorithms Data engineering Data Structures Pandas Spark Communication Skills CI/CD RESTful APIs Mentoring Team management Data modeling Debugging

Posted about 12 hours ago

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