51 to 75 of 199 dbt Jobs

production data systems Strong SQL and Python skills with expertise in large-scale data processing Hands-on experience with modern data stack tools — Airflow, dbt, ClickHouse, BigQuery, Snowflake, or similar Experience with event-driven, real-time or near real-time architectures A first-class approach to data correctness, reliability ...

navigating massive and complex datasets. You can write optimized SQL queries to extract "financial truth". Exposure to other technical skills considered a plus (Dbt, Python, Airflow, BI tools). Foundational Finance Literacy: You don’t need to have a finance/accounting background, but you are comfortable with basic ...

navigating massive and complex datasets. You can write optimized SQL queries to extract "financial truth". Exposure to other technical skills considered a plus (Dbt, Python, Airflow, BI tools). \n Foundational Finance Literacy: You don't need to have a finance/accounting background, but you are comfortable with ...

working with data engineering, data analytics, data visualisation and data science teams using platforms such as Alation, Soda, Microsoft SQL Server, Google Cloud Platform, DBT, Snowflake Cloud Data Platform, Tableau and Dataiku (or similar).\n Join us as we redefine travel experiences and create memories for millions of passengers. ...

ideally at the start of your technical lead journey. Strong proficiency of SQL and advanced Python is required. Experience with modern data stacks, including dbt, data warehousing (e.g. Snowflake) and visualization/semantic layers like Lightdash or Looker. Ability to understand the underlying business logic of marketing and financials ...

LangChain, and writing automation scripts or custom AI agents using node or python. Data Engineering (30%): Experience deploying and maintaining data orchestration toolsets (e.g., dbt, Apache Airflow), ETL/ELT methodologies, real‐time streaming (e.g., AWS Kinesis, Apache Kafka), Vector databases, and RAG architectures. Observability & FinOps: Experience implementing modern observability ...

LangChain, and writing automation scripts or custom AI agents using node or python. Data Engineering (30%): Experience deploying and maintaining data orchestration toolsets (e.g., dbt, Apache Airflow), ETL/ELT methodologies, real‐time streaming (e.g., AWS Kinesis, Apache Kafka), Vector databases, and RAG architectures. Observability & FinOps: Experience implementing modern observability ...

LangChain, and writing automation scripts or custom AI agents using node or python. Data Engineering (30%): Experience deploying and maintaining data orchestration toolsets (e.g., dbt, Apache Airflow), ETL/ELT methodologies, real‐time streaming (e.g., AWS Kinesis, Apache Kafka), Vector databases, and RAG architectures. Observability & FinOps: Experience implementing modern observability ...

LangChain, and writing automation scripts or custom AI agents using node or python. Data Engineering (30%): Experience deploying and maintaining data orchestration toolsets (e.g., dbt, Apache Airflow), ETL/ELT methodologies, real‐time streaming (e.g., AWS Kinesis, Apache Kafka), Vector databases, and RAG architectures. Observability & FinOps: Experience implementing modern observability ...

CLOUD & DATA ECOSYSTEM \n \n Experience in modern cloud data environments (Google Cloud strongly preferred) \n\n \n Familiarity with BigQuery, Analytics Hub, dbt or ELT workflows \n\n \n Understanding of data lineage, quality frameworks, and schema design \n\n \n Comfort navigating multi-source datasets spanning operational, behavioural ...

take work beyond the analysis and get things done. Good to have: Experience in Fintech domain Knowledge of utilities like Airflow/Github/DBT Experience with user-facing products and data *** Please note we are not able to offer visa sponsorship for this level *** Qualifications Additional Information Additional Information ...

analysis and get things done.\n Good to have: \n \n Experience in Fintech domain \n Knowledge of utilities like Airflow/Github/DBT Experience with user-facing products and data\n *** Please note we are not able to offer visa sponsorship for this level *** \n Additional Information ...

practices, mentoring, and thoughtful technical direction. \n Job responsibilities \n \n Design scalable, reusable data processing and data quality frameworks using Python, PySpark, and dbt \nBuild and optimize batch and streaming data pipelines with strong performance, fault tolerance, and observabilityDevelop and operate workflow orchestration (e.g., Apache Airflow) to schedule, monitor … manage data movement and transformationsModel and transform data for analytics using SQL and dbt to support business intelligence and reporting workloadsWrite production-grade Python/PySpark code with disciplined testing, performance tuning, and maintainable object-oriented designImplement infrastructure-as-code (e.g., Terraform) to provision and manage cloud-based data platform ...

Engineering team has recently undergone a technology transformation to \n migrate from our legacy data warehouse to a brand-new data platform (Snowflake + dbt \n + Argo Workflows + Kafka) to better enable the exciting needs of our data stakeholders \n (Data Science, Machine Learning and Business Intelligence, etc. … working with distributed event stores and stream-processing platforms \n such as Kafka of Kinesis. \n ● Experience working with batch processing frameworks, such as DBT, Argo \n Workflows, Apache Airflow, etc. \n ● Familiarity with Docker, Kubernetes, Amazon EKS \n ● Familiarity with Continuous Integration with GitHub Actions \n ● Familiarity with Test ...

stream data processing systems. Experience with Datadog, SQL, Terraform, Docker, AWS (ECS, Kinesis, SQS, CloudWatch), GCP (BigQuery). Knowledge of Airflow, Kafka, Flink, dbt, Kubernetes is highly beneficial. Good understanding of AI platforms, experience building infrastructure for LLM orchestration (e.g., vector databases, RAG pipelines, GPU scaling) is a significant plus. ...

financial services, payments or another regulated industry Hands-on familiarity with the modern data stack, for example Iceberg or Delta, Snowflake or Databricks, and dbt Familiarity with AI governance frameworks such as the EU AI Act, DORA or MAS FEAT Additional Information Find out more How we work: a practical ...

deep understanding of data platform architecture and data modeling. Tooling: Proficiency in SQL, Python, and Databricks is essential. Experience with Snowflake, Sigma, and dbt Cloud is highly preferred. Industry Context: Previous experience in Fintech (small to midsize) or regulated industries (gaming/betting) is a significant advantage. Leadership Style: Proven ...

KPIs critical to how the business measures performance. Beyond surfacing numbers, you’ll build and own the underlying data models and pipelines (in dbt) end-to-end, from raw data to the dashboards leaders rely on. AI Enablement Self-Serve - You’ll help the business get real value from AI. ...

strong technical skillset, especially advanced SQL proficiency to handle complex data manipulation in a modern data warehouse (like Snowflake). Experience with data modeling (dbt) and visualisation tools to create insightful and easy-to-digest dashboards and reports. Proficient with a programming language such as Python or R for data ...

strong technical skillset, especially advanced SQL proficiency to handle complex data manipulation in a modern data warehouse (like Snowflake). Experience with data modeling (dbt) and visualisation tools to create insightful and easy-to-digest dashboards and reports. Proficient with a programming language such as Python or R for data ...

standards, and effective stakeholder engagement Desirable Skills Advanced architectures: Data mesh, data fabric, real‐time/event‐driven systems Modern tools: Databricks, Snowflake, Kafka, dbt Cloud engineering maturity: CI/CD, Infrastructure as Code, DataOps, containers AI/ML enablement: Supporting MLOps and advanced analytics platforms Analytics expertise: BI tools ...

role in building and maintaining core datasets, ensuring data quality and accessibility. Tooling Evangelist : Become the go-to expert for new tooling like dbt & AI applications, leading its adoption and successful rollout across the organization. Best Practices Driver : Strategically assess and implement data modelling best practices within your squad, elevating ...

role in building and maintaining core datasets, ensuring data quality and accessibility. Tooling Evangelist: Become the go-to expert for new tooling like dbt & AI applications, leading its adoption and successful rollout across the organization. Best Practices Driver: Strategically assess and implement data modelling best practices within your squad, elevating ...

hands on Analytics Engineering role with a focus on data modelling and transformation rather than dashboardi ng.Design and develop robust data models using dbt and Databri cksBuild and maintain trusted data layers to support analytics and report ingWork closely with insight analysts to deliver high quality, reliable data ass etsWrite ...

building and scaling AE and Sales Engineering functions in a high‐growth environment. Preferred Qualifications Experience selling into the modern data stack ecosystem (Airflow, dbt, Snowflake, Databricks, Kafka, or similar). Familiarity with open‐source‐led or product‐led growth (PLG) sales motions — understanding how to convert community users into ...