1 to 25 of 77 Remote Apache Airflow Jobs

privacy, and security, ensuring our AI systems are developed and used responsibly and ethically. Tooling the Future: Get hands-on with cutting-edge technologies like Hugging Face, PyTorch, TensorFlow, Apache Spark, Apache Airflow, and other modern data and ML frameworks. Collaborate and Lead: Partner closely with ML Engineers, Data Scientists, and Researchers to understand their data needs … their data, compute, and storage services. Programming Prowess: Strong programming skills in Python and SQL are essential. Big Data Ecosystem Expertise: Hands-on experience with big data technologies like Apache Spark, Kafka, and data orchestration tools such as Apache Airflow or Prefect. ML Data Acumen: Solid understanding of data requirements for machine learning models, including feature engineering More ❯

Data Engineer (AI-Driven SaaS plaform) (Python, Snowflake, Data Modelling, ETL/ELT, Apache Airflow, Kafka, AWS) Large-scale data environment Up to £70,000 plus benefits FULLY REMOTE UK Are you a Data Engineering enthusiast who thrives from designing and implementing robust ETL processes, highly scalable data structures and data pipelines within a truly enterprise-scale data … platform integrates Python and Snowflake and you'll need a deep understanding of SQL and NoSQL databases (MongoDB or similar!) You'll also have exposure with streaming platforms like Apache Kafka and be able to develop and maintain ELT and essentially bring a solid understanding of data warehousing concepts and best practice. Essentially, a strong Data Engineer who is … a Snowflake enthusiast who can write solid SQL queries, within Snowflake! You will understanding Apache Kafka to a high standard and have solid knowledge of Apache Airflow - from a Cloud perspective, good AWS exposure. Naturally you will have good understanding on AWS. I'd love you to be an advocate of Agile too - these guys are massive More ❯

/Automation Language: Python Observability & Monitoring: Monitoring & Alerting: Prometheus, Datadog, Pagerduty Telemetry Standards: OpenTelemetry Application & Data Ecosystem (Supporting): Application Languages/Frameworks: Python, FastAPI, Flask, Node.js, React Data Streaming: Apache Kafka Data Processing/Transformation: Pandas, DBT Workflow Orchestration: Apache Airflow, Ray Machine Learning Stack: Serving: Triton Inference Server MLOps/Experiment Tracking: Weights and Biases, DVC More ❯

Azure Storage, Medallion Architecture, and working with data formats such as JSON, CSV, and Parquet. • Strong understanding of IT concepts, including security, IAM, Key Vault, and networking. • Exposure to Apache Airflow and DBT is a bonus. • Familiarity with agile principles and practices. • Experience with Azure DevOps pipelines. The "Nice to Haves": • Certification in Azure or related technologies. • Experience More ❯

and ops teams. Hard Skills Required Programming & Data Science: Python (Pandas, NumPy, scikit-learn, TensorFlow or PyTorch) essential; R (desirable) Data Engineering & Cloud: Advanced SQL, ETL/ELT tools (Airflow/dbt), AWS/Azure/GCP Machine Learning & AI: Classification, regression, clustering, forecasting; NLP (text mining, sentiment, LLM fine-tuning); GenAI frameworks Analytics & Visualisation: BI tools (Power BI More ❯

mainly remote) Duration: Direct Hire Benefits: Medical/Dental/Vision/401k/PTO/Holidays Job Description: • Design, build, and maintain scalable data pipelines using tools like Apache NiFi, Airflow, or equivalent orchestration systems. • Work with structured and semi-structured data using SQL and NoSQL systems (e.g., PostgreSQL, MongoDB, Elasticsearch, Neo4j). • Develop services and integrations … data pipeline or ETL contexts; Python is a plus. • Proficiency with SQL and NoSQL databases, including query optimization and large dataset processing. • Familiarity with data integration tools such as Apache NiFi, Airflow, or comparable platforms. • Knowledge of RESTful API interactions, JSON parsing, and schema transformations. • Exposure to cloud environments (especially AWS: S3, EC2, Lambda) and distributed systems. • Comfortable More ❯

APIs using FastAPI. Experience using Trino for query optimization and distributed SQL processing. Proficiency in working with Parquet Files for efficient data storage and retrieval. Hands-on experience with Airflow for orchestrating complex data workflows. Familiarity with Databricks Medallion model. Familiarity with OpenMetaData for metadata management and data governance. Experience working with streaming and batch data processing frameworks is More ❯

computing, with experience using frameworks like Databricks Strong experience with Azure or other cloud platforms (AWS) Strong experience building data pipelines or ETL tools and Orchestration frameworks such as Airflow Strong experience and appreciation of CI/CD implementation Good experience with implementing automated testing Good experience with Infrastructure as Code with Terraform Strong understanding of Agile delivery methodologies More ❯

in Kubernetes (AWS EKS, Rancher) with CI/CD Apply DevSecOps + security-first practices from design to delivery Tech You'll Touch AWS Python FastAPI Node.js React Terraform Apache Airflow Trino Spark Hadoop Kubernetes You Have Active Secret Clearance 3+ years in Agile, cloud-based data engineering Experience with API design, ORM + SQL, AWS data services More ❯

teams. Awareness of ethical considerations and responsible AI practices. Excellent problem-solving skills, attention to detail, and ability to thrive in a fast-paced, collaborative environment. Familiarity with NiFi, Airflow, or other data pipeline orchestration tools (not required, nice to have). Exposure to Kubernetes, IAM/security models, or Spark/Kafka environments (not required, nice to have More ❯

data modelling techniques (star schema, data vault, dimensional modelling). Proficiency in Excel-based data workflows for various Agile Retail projects. Hands-on experience with data pipeline orchestration tools (Airflow, dbt, Prefect, or similar). Benefits: Unlimited holiday Annual Wellbeing Allowance Flexible work culture Monthly socials and events Complimentary snack bar Employer pension contribution If you're a data More ❯

data modelling techniques (star schema, data vault, dimensional modelling). Proficiency in Excel-based data workflows for various Agile Retail projects. Hands-on experience with data pipeline orchestration tools (Airflow, dbt, Prefect, or similar). Benefits: Unlimited holiday Annual Wellbeing Allowance Flexible work culture Monthly socials and events Complimentary snack bar Employer pension contribution If you're a data More ❯

Functions) Strong proficiency in SQL, Python, and data modeling for analytical and operational use cases Hands-on experience with production-grade ETL/ELT frameworks and workflow orchestration (e.g., Airflow, dbt, Talend, AWS Glue, GCP Dataform/Cloud Composer) Proven ability to design, deploy, and optimize data warehouses and lakehouse architectures using technologies like BigQuery, Redshift, Snowflake, and Databricks More ❯

Tech Stack Cloud: Azure, sometimes GCP & AWS Data Platform: Databricks, Snowflake, BigQuery Data Engineering tools: Pyspark, Polars, DuckDB, Malloy, SQL Infrastructure-as-code: Terraform, Pulumi Data Management and Orchestration: Airflow, dbt Databases and Data Warehouses: SQL Server, PostgreSQL, MongoDB, Qdrant, Pinecone GenAI: OpenAI APIs, HuggingFace, LangChain, Talk-to-data Monitoring: Datadog About You We are looking for someone who More ❯

for internal tooling Experience with real-time data processing and analytics Background in building developer tools or internal platforms Familiarity with AI/ML operations (MLOps) practices (Experience using airflow) Experience building MCP servers and integrating with AI assistants Knowledge of structured data exchange protocols and API design for AI systems. Location: Austin, TX (Hybrid; Tues-Thurs onsite) Duration More ❯

experience in data engineering, warehousing, or platform leadership. Proven track record of delivering large-scale data warehouse migrations (BigQuery experience strongly preferred). Hands-on expertise with SQL, Python, Airflow, DBT/Dataform, Terraform , and modern data architecture. Strong leadership and stakeholder management skills. Experience driving complex data projects in agile, cross-functional teams. Nice-to-haves: Background in More ❯

charts. BI tools. Desirable PowerBI A/B testing. Split principles, test planning, logging. Desirable hard skills Python. Data analysis, pandas, numpy, scipy, statsmodels, seaborn, matplotlib etc. ETL processes. Airflow, Pentaho etc. IT understanding. Client-server processes. API. Back-end and front-end. Parsing. Algorithms and data structures. Management. Sprints, AGILE. Waterfall. Jira etc. Other skills Required fluent English. More ❯

charts. BI tools. Desirable PowerBI A/B testing. Split principles, test planning, logging. Desirable hard skills Python. Data analysis, pandas, numpy, scipy, statsmodels, seaborn, matplotlib etc. ETL processes. Airflow, Pentaho etc. IT understanding. Client-server processes. API. Back-end and front-end. Parsing. Algorithms and data structures. Management. Sprints, AGILE. Waterfall. Jira etc. Other skills Required fluent English. More ❯

record of building and managing talent pipelines in competitive markets. Technical Understanding Solid grasp of modern tech stacks including Python, React.js, cloud platforms (AWS, Azure), and data tools (dbt, Airflow, Snowflake) from a recruitment perspective. Ability to assess technical skills through structured interviews and practical assessments. Understanding of software development practices, agile methodologies, and DevOps culture. Familiarity with AI More ❯

improvement and operational excellence. Deep expertise in data compliance frameworks, cost management, and platform optimisation. Strong hands-on experience with modern cloud data warehouses (Databricks, Snowflake, AWS), SQL, Spark, Airflow, Terraform. Advanced Python skills with orchestration tooling; solid experience in CI/CD (Git, Jenkins). Proven track record in data modelling, batch/real-time integration, and large More ❯

members to deliver outcome Highly motivated, with strong problem-solving skills and business acumen Desirable Skills Experience with data visualization tools (e.g., Looker, Tableau, Power BI) Familiarity with dbt, Airflow, or other modern data tools Exposure to marketing or e-commerce industries Additional Information Publicis Groupe operates a hybrid working pattern with full time employees being office-based three More ❯

applicable. Essential Skills & Experience Proven experience owning and operating production data platforms within AWS. Strong understanding of AWS core services: EventBridge, Lambda, EC2, S3, and MWAA (Managed Workflows for Apache Airflow). Experience with infrastructure reliability, observability tooling, and platform automation. Solid experience with CI/CD pipelines, preferably Bitbucket Pipelines. Familiarity with Snowflake administration and deployment practices. More ❯

fine-tuning techniques including LoRA, QLoRA, and parameter efficient methods - Multi-modal AI systems combining text, image, and structured data - Reinforcement Learning from Human Feedback (RLHF) for model alignment - Apache Airflow/Dagster for ML workflow orchestration and ETL pipeline management - Model versioning and experiment tracking (MLflow, Weights & Biases) - Real-time model serving and edge deployment strategies - A More ❯

fine-tuning techniques including LoRA, QLoRA, and parameter efficient methods - Multi-modal AI systems combining text, image, and structured data - Reinforcement Learning from Human Feedback (RLHF) for model alignment - Apache Airflow/Dagster for ML workflow orchestration and ETL pipeline management - Model versioning and experiment tracking (MLflow, Weights & Biases) - Real-time model serving and edge deployment strategies - A More ❯

fine-tuning techniques including LoRA, QLoRA, and parameter efficient methods - Multi-modal AI systems combining text, image, and structured data - Reinforcement Learning from Human Feedback (RLHF) for model alignment - Apache Airflow/Dagster for ML workflow orchestration and ETL pipeline management - Model versioning and experiment tracking (MLflow, Weights & Biases) - Real-time model serving and edge deployment strategies - A More ❯