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 ❯
engineering, or similar roles. Hands-on expertise with Python (Numpy/Pandas) and SQL. Proven experience designing and building robust ETL/ELT pipelines (dbt, Airflow). Strong knowledge of data pipelining, schema design, and cloud platforms (e.g., Snowflake, AWS). Excellent communication skills and the ability to translate technical More ❯
use. Your typical day will look like this: Connect with team at standup to catchup on the latest. Builddata pipelines with Spark or DBT on Starburst Use SQL to transform data into meaningful insights Build and deploy infrastructure with Terraform Implement DDL, DML with Iceberg Do code reviews for More ❯
. Experience deploying and maintaining cloud infrastructure (e.g. AWS, GCP, or Azure). Familiarity with data modeling and warehousing concepts, and dimensional modeling techniques. dbt knowledge is preferable. Comfortable working with CI/CD tools, version control, and containers (e.g Git, Jenkins, Docker). Understanding of data governance, security best 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 ❯
Bristol, Gloucestershire, United Kingdom Hybrid / WFH Options
Lloyds Bank plc
Agile environment. Deep technical expertise in software and data engineering, programming languages (python, java etc.). Understanding of orchestration (Composer, DAGs), data processing (DataFlow, dbt), and database capabilities (e.g. BigQuery, CloudSQL, BigTable). Knowledge of container technologies (Docker, Kubernetes), IaaC (Terraform) and experience with cloud platforms such as GCP. Detailed 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 ❯
working autonomously. It would be a real bonus, but not a requirement if: You've worked in a start-up environment. You've got DBT experience. You've familiarity with MLOps principles and practices and their application in a production setting. Interview Process: You'll have a 20-minute conversation More ❯
R. Working knowledge of message queuing and stream processing. Experience with Apache Spark or Similar Technologies. Experience with Agile and Scrum Technologies. Familiarity with dbt and Airflow is an advantage. Experience working in a start-up or scale up environment. Experience working in the fields of financial technology, traditional financial More ❯
ML infrastructure, particularly GCP (Vertex AI, BigQuery), or equivalent (e.g. AWS, Azure) Exposure to orchestration tools such as Kubeflow pipelines or Airflow Familiarity with DBT or similar tools for modelling data in data warehouses Desire to build interpretable and explainable ML models (using techniques such as SHAP) Desire to quantify More ❯
Redshift, BigQuery, or Snowflake, and modern transformation/query engines like Spark, Flink, Trino. Familiarity with workflow management tools (e.g., Airflow) and/or dbt for transformations. Comprehensive understanding of modern data platforms, including data governance and observability. Experience with cloud platforms (AWS, GCP, Azure). Self-starter capable of More ❯
languages commonly used for data work (e.g., Python, Java, Scala) Deep understanding of ETL/ELT tools and workflow orchestration platforms (e.g., Airflow, Fivetran, dbt) Proficiency with SQL and solid grounding in data modeling concepts Familiarity with cloud services and architectures (AWS, GCP, or Azure) Proven experience managing or mentoring More ❯
languages commonly used for data work (e.g., Python, Java, Scala) Deep understanding of ETL/ELT tools and workflow orchestration platforms (e.g., Airflow, Fivetran, dbt) Proficiency with SQL and solid grounding in data modeling concepts Familiarity with cloud services and architectures (AWS, GCP, or Azure) Proven experience managing or mentoring More ❯
driving innovation in analytics engineering practices. What You'll Own Technical Leadership: Lead the design and implementation of robust data pipelines using tools like dbt and Airflow. Client Collaboration: Build strong relationships with stakeholders to identify challenges and deliver tailored solutions. Data Excellence: Transform raw data into actionable datasets for More ❯
and technologies (note we do not expect applicants to have prior experience of all them): Google Cloud Platform for all of our analytics infrastructure dbt and BigQuery SQL for our data modelling and warehousing Python for data science Go to write our application code AWS for most of our backend More ❯
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.) Passion for More ❯
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 ❯
Stack Python and Scala Starburst and Athena Kafka and Kinesis DataHub ML Flow and Airflow Docker and Terraform Kafka, Spark, Kafka Streams and KSQL DBT AWS, S3, Iceberg, Parquet, Glue and EMR for our Data Lake Elasticsearch and DynamoDB More information: Enjoy fantastic perks like private healthcare & dental insurance, a More ❯
Have hands-on experience with cloud infrastructure (GCP/AWS/Azure), infrastructure-as-code (Terraform), containerisation (Docker/k8s) and data pipelines (SQL, dbt, Airbyte) Love automation, process improvement and finding ways to help others work efficiently Are comfortable working autonomously and taking responsibility for the delivery of large More ❯
Snowflake/Databricks/Redshift/BigQuery, including performance tuning and optimisation. Understanding of best practices for designing scalable and efficient data models, leveraging dbt for transformations. Familiarity with CircleCI, Terraform or similar tools for deployment and infrastructure as code. In this role, you will be responsible for: Shipping and More ❯
or a related field, with a focus on building scalable data systems and platforms. Expertise in modern data tools and frameworks such as Spark, dbt, Airflow, Kafka, Databricks, and cloud-native services (AWS, GCP, or Azure) Understanding of data modeling, distributed systems, ETL/ELT pipelines, and streaming architectures Proficiency More ❯
Tools). Experience with one or more of the following is a plus: Kubernetes, Prometheus, Argo workflows, GitHub Actions, Elasticsearch/Opensearch, PostgreSQL, BigQuery, DBTdata pipelines, Fastly, Storybook, Contentful, Deno, Bun. Benefits We want to give you a great work environment; contribute back to both your personal and professional More ❯
