51 to 75 of 382 Remote Apache Airflow Jobs

adopt emerging technologies, and enhance analytics capabilities. Requirements: Technical Proficiency : Hands-on experience building ETL/ELT pipelines with Python, SQL, or tools like Apache Airflow, and expertise in visualisation tools (Power BI, Tableau, or Looker). Cloud Expertise : Familiarity with cloud platforms like Snowflake, Databricks, or AWS More ❯

to Have: Familiarity with cloud platforms (AWS, GCP, Azure) and cloud-based database services (Snowflake). Knowledge of data warehousing, orchestration and pipeline technologies (Apache Airflow/Kafka, Azure DataFactory etc.). Experience with DBT for modelling Server administration and networking fundamentals More ❯

to Have: Familiarity with cloud platforms (AWS, GCP, Azure) and cloud-based database services (Snowflake). Knowledge of data warehousing, orchestration and pipeline technologies (Apache Airflow/Kafka, Azure DataFactory etc.). Experience with DBT for modelling Server administration and networking fundamentals More ❯

or a similar language. Proficiency in database technologies (SQL, NoSQL, time-series databases) and data modelling. Strong understanding of data pipeline orchestration tools (e.g., Apache Airflow, Kubernetes). You thrive when working as part of a team. Comfortable in a fast-paced environment. Have excellent written and verbal More ❯

or Java (Required) Bachelor's degree or equivalent in Computer Science, Mathematics or Finance-related field (Required) Knowledge of workflow management frameworks such as Apache Airflow (Preferred) Knowledge of cloud computing infrastructure, such as AWS (Preferred) Knowledge of BI visualisation tools such as Looker or Power BI (Preferred More ❯

engineering or a related field Proficiency in English spoken and written Nice-to-Haves: Experience with ETL/ELT pipeline design and tools (e.g., Apache Airflow). Familiarity with Change Data Capture (CDC) solutions. Knowledge of database services on other cloud platforms (e.g., Azure SQL Database, Google Cloud More ❯

engineering or a related field Proficiency in English spoken and written Nice-to-Haves: Experience with ETL/ELT pipeline design and tools (e.g., Apache Airflow). Familiarity with Change Data Capture (CDC) solutions. Knowledge of database services on other cloud platforms (e.g., Azure SQL Database, Google Cloud More ❯

integrate data best practices across teams Champion data quality, governance, and documentation Key Requirements: Strong experience with Python, SQL, and modern ETL tools (e.g., Airflow, dbt) Solid grasp of cloud platforms (AWS/GCP/Azure) and data warehouses (e.g., BigQuery, Snowflake) Familiarity with streaming technologies (Kafka, Kinesis, etc. More ❯

integrate data best practices across teams Champion data quality, governance, and documentation Key Requirements: Strong experience with Python, SQL, and modern ETL tools (e.g., Airflow, dbt) Solid grasp of cloud platforms (AWS/GCP/Azure) and data warehouses (e.g., BigQuery, Snowflake) Familiarity with streaming technologies (Kafka, Kinesis, etc. More ❯

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 More ❯

like Git. Strong problem-solving skills and the ability to work in a fast-paced, collaborative environment. Preferred Qualifications: Experience with tools such as Airflow, Fivetran, or Cloud Composer. Familiarity with cloud platforms such as AWS, GCP, or Azure. Experience in financial, healthcare, or retail data environments (optional). More ❯

like Git. Strong problem-solving skills and the ability to work in a fast-paced, collaborative environment. Preferred Qualifications: Experience with tools such as Airflow, Fivetran, or Cloud Composer. Familiarity with cloud platforms such as AWS, GCP, or Azure. Experience in financial, healthcare, or retail data environments (optional). More ❯

transformation, cleaning, and loading. Strong coding experience with Python and Pandas. Experience with any flavour of data pipeline and workflow management tools: Dagster, Celery, Airflow, etc. Build processes supporting data transformation, data structures, metadata, dependency and workload management. Experience supporting and working with cross-functional teams in a dynamic More ❯

peer to peer feedback and evolving healthy, curious and humble teams. Tech Stack: Python, Javascript/Typescript, React/React Native, AWS, GraphQL, Snowflake, Airflow, DDD. This is an incredible opportunity for a Senior Software Engineer to join a unique company as they embark on a period of significant More ❯

peer to peer feedback and evolving healthy, curious and humble teams. Tech Stack: Python, Javascript/Typescript, React/React Native, AWS, GraphQL, Snowflake, Airflow, DDD. This is an incredible opportunity for a Senior Software Engineer to join a unique company as they embark on a period of significant More ❯

skills for data transformation, cleaning, and loading. Strong coding experience with Python and Pandas. Experience of data pipeline and workflow management tools: Dagster, Celery, Airflow, etc. Build processes supporting data transformation, data structures, metadata, dependency and workload management. Experience supporting and working with cross-functional teams in a dynamic More ❯

related field, with a focus on building scalable data systems and platforms. Strong expertise with modern data tools and frameworks such as Spark , dbt , Airflow , Kafka , Databricks , and cloud-native services (AWS, GCP, or Azure). Deep understanding of data modeling , distributed systems , streaming architectures , and ETL/ELT More ❯

in Python. Familiarity with analytical data warehouses (e.g. Redshift preferred, or Snowflake/BigQuery). Understanding of orchestration tools such as AWS Step Functions, Airflow, or AWS Batch. Experience working with Agile methodologies. Awareness of automated testing and delivery pipelines. Understanding of metadata-driven data modelling or scalable data More ❯

help you get there: Understanding of cloud computing security concepts Proficiency with IaC tools like Terraform or CloudFormation. Experience with workflow orchestration tools (e.g., Airflow, Dagster). Good understanding of Cloud providers – AWS, Microsoft Azure, Google Cloud Familiarity with DBT, Delta Lake, Databricks Experience working in Agile environments with More ❯

help you get there: Understanding of cloud computing security concepts Proficiency with IaC tools like Terraform or CloudFormation. Experience with workflow orchestration tools (e.g., Airflow, Dagster). Good understanding of Cloud providers – AWS, Microsoft Azure, Google Cloud Familiarity with DBT, Delta Lake, Databricks Experience working in Agile environments with More ❯

in python Comfortable implementing data architectures in analytical data warehouses such as Snowflake, Redshift or BigQuery Hands on experience with data orchestrators such as Airflow Knowledge of Agile development methodologies Awareness of cloud technology particularly AWS. Knowledge of automated delivery processes Hands on experience of best engineering practices (handling More ❯

help you get there: Understanding of cloud computing security concepts Proficiency with IaC tools like Terraform or CloudFormation. Experience with workflow orchestration tools (e.g., Airflow, Dagster). Good understanding of Cloud providers – AWS, Microsoft Azure, Google Cloud Familiarity with DBT, Delta Lake, Databricks Experience working in Agile environments with More ❯

. •Familiarity with data cataloguing tools and practices. •Prior experience in a startup or high-growth tech company. •Familiarity with containerisation (Docker), orchestration tools (Airflow, Prefect), and CI/CD workflows. •Understanding of foundational MLOps and data-centric AI practices. •Experience of working in an Agile environment. What We More ❯

for data processing, analysis and automation. Proficiency in building and maintaining batch and streaming ETL/ELT pipelines at scale, employing tools such as Airflow, Fivetran, Kafka, Iceberg, Parquet, Spark, Glue for developing end-to-end data orchestration leveraging on AWS services to ingest, transform and process large volumes More ❯

for data processing, analysis and automation. Proficiency in building and maintaining batch and streaming ETL/ELT pipelines at scale, employing tools such as Airflow, Fivetran, Kafka, Iceberg, Parquet, Spark, Glue for developing end-to-end data orchestration leveraging on AWS services to ingest, transform and process large volumes More ❯