variety of databases Working knowledge of one or more of the cloud platforms (AWS, Azure, GCP) Experience building ETL/ELT pipelines specifically using DBT for structured and semi-structured datasets Any orchestration toolings such as Airflow, Dagster, Azure Data Factory, Fivetran etc It will be nice to have: Software More ❯
variety of databases Working knowledge of one or more of the cloud platforms (AWS, Azure, GCP) Experience building ETL/ELT pipelines specifically using DBT for structured and semi-structured datasets Any orchestration toolings such as Airflow, Dagster, Azure Data Factory, Fivetran etc It will be nice to have: Software More ❯
data solutions using API and microservice-based architecture. Deep understanding of ETL/ELT architecture, streaming, and event-driven processing; familiarity with tools like dbt, Airflow, Kafka, or equivalents. Familiarity with mid-sized firm tech stacks, especially in financial services, including systems such as NetSuite, Salesforce, Addepar, Experience with Atlassian More ❯
data solutions using API and microservice-based architecture. Deep understanding of ETL/ELT architecture, streaming, and event-driven processing; familiarity with tools like dbt, Airflow, Kafka, or equivalents. Familiarity with mid-sized firm tech stacks, especially in financial services, including systems such as NetSuite, Salesforce, Addepar, Experience with Atlassian More ❯
platform roles, including at least 3 years in a leadership position. Deep hands-on expertise in modern data architecture, pipelines, and tooling (e.g., Airflow, DBT, Kafka, Spark, Python, SQL). Strong understanding of cloud infrastructure (AWS, GCP, or Azure) and scalable data systems. Familiarity with analytics and ML workflows, including More ❯
platform roles, including at least 3 years in a leadership position. Deep hands-on expertise in modern data architecture, pipelines, and tooling (e.g., Airflow, DBT, Kafka, Spark, Python, SQL). Strong understanding of cloud infrastructure (AWS, GCP, or Azure) and scalable data systems. Familiarity with analytics and ML workflows, including More ❯
platform roles, including at least 3 years in a leadership position. Deep hands-on expertise in modern data architecture, pipelines, and tooling (e.g., Airflow, DBT, Kafka, Spark, Python, SQL). Strong understanding of cloud infrastructure (AWS, GCP, or Azure) and scalable data systems. Familiarity with analytics and ML workflows, including More ❯
platform roles, including at least 3 years in a leadership position. Deep hands-on expertise in modern data architecture, pipelines, and tooling (e.g., Airflow, DBT, Kafka, Spark, Python, SQL). Strong understanding of cloud infrastructure (AWS, GCP, or Azure) and scalable data systems. Familiarity with analytics and ML workflows, including More ❯
platform roles, including at least 3 years in a leadership position. Deep hands-on expertise in modern data architecture, pipelines, and tooling (e.g., Airflow, DBT, Kafka, Spark, Python, SQL). Strong understanding of cloud infrastructure (AWS, GCP, or Azure) and scalable data systems. Familiarity with analytics and ML workflows, including More ❯
platform roles, including at least 3 years in a leadership position. Deep hands-on expertise in modern data architecture, pipelines, and tooling (e.g., Airflow, DBT, Kafka, Spark, Python, SQL). Strong understanding of cloud infrastructure (AWS, GCP, or Azure) and scalable data systems. Familiarity with analytics and ML workflows, including More ❯
platform roles, including at least 3 years in a leadership position. Deep hands-on expertise in modern data architecture, pipelines, and tooling (e.g., Airflow, DBT, Kafka, Spark, Python, SQL). Strong understanding of cloud infrastructure (AWS, GCP, or Azure) and scalable data systems. Familiarity with analytics and ML workflows, including More ❯
platform roles, including at least 3 years in a leadership position. Deep hands-on expertise in modern data architecture, pipelines, and tooling (e.g., Airflow, DBT, Kafka, Spark, Python, SQL). Strong understanding of cloud infrastructure (AWS, GCP, or Azure) and scalable data systems. Familiarity with analytics and ML workflows, including More ❯
platform roles, including at least 3 years in a leadership position. Deep hands-on expertise in modern data architecture, pipelines, and tooling (e.g., Airflow, DBT, Kafka, Spark, Python, SQL). Strong understanding of cloud infrastructure (AWS, GCP, or Azure) and scalable data systems. Familiarity with analytics and ML workflows, including More ❯
platform roles, including at least 3 years in a leadership position. Deep hands-on expertise in modern data architecture, pipelines, and tooling (e.g., Airflow, DBT, Kafka, Spark, Python, SQL). Strong understanding of cloud infrastructure (AWS, GCP, or Azure) and scalable data systems. Familiarity with analytics and ML workflows, including More ❯
platform roles, including at least 3 years in a leadership position. Deep hands-on expertise in modern data architecture, pipelines, and tooling (e.g., Airflow, DBT, Kafka, Spark, Python, SQL). Strong understanding of cloud infrastructure (AWS, GCP, or Azure) and scalable data systems. Familiarity with analytics and ML workflows, including More ❯
platform roles, including at least 3 years in a leadership position. Deep hands-on expertise in modern data architecture, pipelines, and tooling (e.g., Airflow, DBT, Kafka, Spark, Python, SQL). Strong understanding of cloud infrastructure (AWS, GCP, or Azure) and scalable data systems. Familiarity with analytics and ML workflows, including More ❯
platform roles, including at least 3 years in a leadership position. Deep hands-on expertise in modern data architecture, pipelines, and tooling (e.g., Airflow, DBT, Kafka, Spark, Python, SQL). Strong understanding of cloud infrastructure (AWS, GCP, or Azure) and scalable data systems. Familiarity with analytics and ML workflows, including More ❯
platform roles, including at least 3 years in a leadership position. Deep hands-on expertise in modern data architecture, pipelines, and tooling (e.g., Airflow, DBT, Kafka, Spark, Python, SQL). Strong understanding of cloud infrastructure (AWS, GCP, or Azure) and scalable data systems. Familiarity with analytics and ML workflows, including More ❯
platform roles, including at least 3 years in a leadership position. Deep hands-on expertise in modern data architecture, pipelines, and tooling (e.g., Airflow, DBT, Kafka, Spark, Python, SQL). Strong understanding of cloud infrastructure (AWS, GCP, or Azure) and scalable data systems. Familiarity with analytics and ML workflows, including More ❯
platform roles, including at least 3 years in a leadership position. Deep hands-on expertise in modern data architecture, pipelines, and tooling (e.g., Airflow, DBT, Kafka, Spark, Python, SQL). Strong understanding of cloud infrastructure (AWS, GCP, or Azure) and scalable data systems. Familiarity with analytics and ML workflows, including More ❯
platform roles, including at least 3 years in a leadership position. Deep hands-on expertise in modern data architecture, pipelines, and tooling (e.g., Airflow, DBT, Kafka, Spark, Python, SQL). Strong understanding of cloud infrastructure (AWS, GCP, or Azure) and scalable data systems. Familiarity with analytics and ML workflows, including More ❯
platform roles, including at least 3 years in a leadership position. Deep hands-on expertise in modern data architecture, pipelines, and tooling (e.g., Airflow, DBT, Kafka, Spark, Python, SQL). Strong understanding of cloud infrastructure (AWS, GCP, or Azure) and scalable data systems. Familiarity with analytics and ML workflows, including More ❯
platform roles, including at least 3 years in a leadership position. Deep hands-on expertise in modern data architecture, pipelines, and tooling (e.g., Airflow, DBT, Kafka, Spark, Python, SQL). Strong understanding of cloud infrastructure (AWS, GCP, or Azure) and scalable data systems. Familiarity with analytics and ML workflows, including More ❯
platform roles, including at least 3 years in a leadership position. Deep hands-on expertise in modern data architecture, pipelines, and tooling (e.g., Airflow, DBT, Kafka, Spark, Python, SQL). Strong understanding of cloud infrastructure (AWS, GCP, or Azure) and scalable data systems. Familiarity with analytics and ML workflows, including More ❯
platform roles, including at least 3 years in a leadership position. Deep hands-on expertise in modern data architecture, pipelines, and tooling (e.g., Airflow, DBT, Kafka, Spark, Python, SQL). Strong understanding of cloud infrastructure (AWS, GCP, or Azure) and scalable data systems. Familiarity with analytics and ML workflows, including More ❯
