16 of 16 Permanent Great Expectations Jobs

reliability across our sports technology ecosystem. What Your Day Will Look Like Build scalable and robust frameworks for validating complex data systems, pipelines, and APIs using tools like Pandas, Great Expectations, and Java modules. Collaborate with development teams to design and implement automated tests for microservices, emphasizing Spring Boot and Java-based architectures. Implement testing strategies for AWS … CI/CD pipelines for seamless build and deployment cycles. Strong programming skills in Python, with additional experience in SQL and scripting for data manipulation and validation. Familiarity with Great Expectations (or similar), Postman, and synthetic data generation frameworks. Expertise in identifying testing gaps, proposing enhancements, and fostering a culture of data quality and continuous improvement across teams. More ❯

e.g. Flink, Hadoop, Beam) Familiarity with Databricks as a data and AI platform or the Lakehouse Architecture. Experience with data quality and/or and data lineage frameworks like Great Expectations, dbt data quality, OpenLineage or Marquez, and data drift detection and alerting. Understanding of Data Management principles (security and data privacy) and how they can be applied … Excellent staff travel benefits About easyJet At easyJet our aim is to make low-cost travel easy - connecting people to what they value using Europe's best airline network, great value fares, and friendly service. It takes a real team effort to carry over 90 million passengers a year across 35 countries. Whether you're working as part of More ❯

Azure Data Factory, Synapse Analytics, or ADLS . Proficiency in SQL and scripting languages (e.g., Python, Scala) for data validation and test automation. Experience with test automation frameworks (e.g., Great Expectations, DBT tests, PyTest, or similar ). Exposure to CI/CD testing within Azure DevOps, GitHub Actions, or Jenkins . Understanding of data governance, data security, and More ❯

experience with workflow orchestration tools such as Airflow. Strong version control and DevOps exposure (Git, GitHub Actions, Terraform). Familiar with data quality tools and metadata/cataloguing (e.g. Great Expectations, Unity Catalog). Beneficial: MarTech domain knowledge. Notable: This is a hybrid engagement represented by 2 days/week onsite, either in Central London or Glasgow. You More ❯

Engines: Strong with RDBMS (PostgreSQL, MySQL), NoSQL (DynamoDB, Cassandra), data lakes (Parquet, ORC), and warehouse paradigms. Observability & Quality: Deep familiarity with metrics, logging, tracing, and data quality tools (e.g., Great Expectations, Monte Carlo, custom validation/test suites). Security & Governance: Data encryption, secrets management, RBAC/ABAC, and compliance awareness (GDPR, CCPA). CI/CD for More ❯

medallion architecture or comparable frameworks. Experience in workflow orchestration using Flyte, dbt, Airflow, or Prefect. Strong understanding of unit, integration, and data validation testing using tools like Pytest or Great Expectations. Familiarity with cloud infrastructure (preferably Azure) for managing pipelines and storage Ability to collaborate closely with stakeholders to understand requirements and shape data pipelines to meet user needs More ❯

environment. • Model data using Kimball/star schemas and data vault principles to support BI and self service analytics. • Implement data quality, lineage, and observability tooling (e.g., dbt tests, Great Expectations, Azure Purview). • Optimise storage and compute costs through partitioning, incremental loads, and automation. • Collaborate with DevOps to embed CI/CD and Infrastructure as Code (Terraform More ❯

needs. Experience with data ingestion tools, like Fivetran. Advantageous Exposure to deploying applications with Kubernetes. Experience with Data Orchestrator tools (Airflow, Prefect, etc.) Experience with Data Observability tools (Montecarlo, Great Expectations, etc.) Experience with Data Catalog tools (Amundsen, OpenMetadata, etc.) Interview Process Call with the talent team Take home task Tech interview CPTO interview Life at Lendable The More ❯

and managing a feature store , and driving best practices for feature engineering in production systems . - Proficiency in model testing strategies , including unit testing for pipelines, data validation (e.g., Great Expectations, Deequ), and A/B or shadow testing. - Experience with model monitoring frameworks - Solid knowledge of CI/CD for ML , including automated training and deployment workflows. More ❯

over 700 professionals, partnering with 800+ sector leaders. People come first always we are incredibly proud of our unparalleled work culture. Not just words on paper, we wear our "Great Place to Work" certifications from the UK and India like badges of honour. Dive into an ocean of opportunities in an atmosphere that celebrates collaboration. Sharpen your prowess with … in an Azure ecosystem. Required Experience: • Creating mapping specifications between legacy and CRM, ERP, Finance applications • Integration to D365, Dataverse solutions or other SaaS applications • Data Quality Frameworks: Soda.io, Great Expectations, DBT • Creation of fault-tolerant data ingestion pipelines in SSIS/KWS/Data Factory/data flows using Linked Services, Integration Datasets • Extracting data from a … they leverage technology, working with public bodies to shape digital services and working with top tier private entities to bring genuinely new and meaningful products and services to market. • Great Benefits - all the usual suspects and then some. Some highlights include our choose-your-own tech approach to end-user devices, well stocked cupboards with tasty goodies (we're More ❯

over 700 professionals, partnering with 800+ sector leaders. People come first always we are incredibly proud of our unparalleled work culture. Not just words on paper, we wear our "Great Place to Work" certifications from the UK and India like badges of honour. Dive into an ocean of opportunities in an atmosphere that celebrates collaboration. Sharpen your prowess with … in an Azure ecosystem. Required Experience: Creating mapping specifications between legacy and CRM, ERP, Finance applications Integration to D365, Dataverse solutions or other SaaS applications Data Quality Frameworks: Soda.io, Great Expectations, DBT Creation of fault-tolerant data ingestion pipelines in SSIS/KWS/Data Factory/data flows using Linked Services, Integration Datasets Extracting data from a … they leverage technology, working with public bodies to shape digital services and working with top tier private entities to bring genuinely new and meaningful products and services to market. Great Benefits – all the usual suspects and then some. Some highlights include our choose-your-own tech approach to end-user devices, well stocked cupboards with tasty goodies (we’re More ❯

data quality, lineage, cataloging, and contract enforcement. -Collaborate with data engineers and architects to deliver scalable pipelines. -Own roadmap and tooling integration for Alation, Databricks, Azure Data Services, and Great Expectations. -Partner with Data Governance to support domain stewards and ensure enterprise alignment. Ideal Experience: -Product ownership of data pipelines, platforms, or PaaS. -Familiarity with Azure, Databricks, and enterprise More ❯

enforce data quality, lineage, and contracts during platform migration. Partner with engineers and architects to build scalable, validated pipelines . Integrate tooling across Alation, Azure Data Services, Databricks , and Great Expectations . Align with Data Governance to support data domain stewards during migration. 💼 You Bring: Proven track record delivering data platform and migration initiatives as a Product Manager. More ❯

enforce data quality, lineage, and contracts during platform migration. Partner with engineers and architects to build scalable, validated pipelines . Integrate tooling across Alation, Azure Data Services, Databricks , and Great Expectations . Align with Data Governance to support data domain stewards during migration. 💼 You Bring: Proven track record delivering data platform and migration initiatives as a Product Manager. More ❯

lineage, cataloguing, and data contract enforcement. Collaborate closely with data engineers and architects to deliver scalable, reliable pipelines. Drive roadmap and integrations across Alation, Azure Data Services, Databricks, and Great Expectations. Partner with Data Governance to support data domain stewards and align with enterprise data strategy. Ideal Experience: Proven experience as a Product Manager for data platforms, pipelines, or More ❯

lineage, cataloguing, and data contract enforcement. Collaborate closely with data engineers and architects to deliver scalable, reliable pipelines. Drive roadmap and integrations across Alation, Azure Data Services, Databricks, and Great Expectations. Partner with Data Governance to support data domain stewards and align with enterprise data strategy. Ideal Experience: Proven experience as a Product Manager for data platforms, pipelines, or More ❯