Endava
Information Technology And Services
DataEngineer
Neural analysis suggests this role is
optimal for mid candidates.
“Data Engineer at Endava. Skills: GCP, BigQuery, AWS, Python, SQL, dbt, Airflow. Design data pipelines. Build data pipelines”
What You'll Achieve.
deliver scalable, secure, analytics-ready data pipelines; deliver scalable, secure, analytics-ready data models
Industry & Context.
problem-solving capability; troubleshooting pipeline failures; performance issues
What They're Looking For.
Must Have
GCP, BigQuery, Cloud Storage, Apache Airflow, dbt, Python, SQL, data pipelines, ingestion, transformation, Gititbucket, data quality checks, AWS, GCP, IAM roles and policies, Lambda, S3, RDS, Redshift, BigQuery, workload optimisation, cost management, data pipelines, SQL, analytical and window functions, dbt Cloud, Airflow workflow design, CI/CD, GitHub Actions, Bamboo, Terraform, CloudFormation, data quality frameworks, automated testing of pipelines, Python, data modelling, facts/dimensions, SCD patterns, performance optimisation, cloud security best practices, least-privilege IAM, data access controls, regulated environments, governance expectations, Agile delivery frameworks, JIRA, Confluence, problem-solving capability, troubleshooting pipeline failures, performance issues, supporting production environments, incident response, root-cause analysis
Nice to Have
Dataplex, Collibra integration, CI/CD, Grafana, Splunk, Power BI data preparation, financial services data, Terraform, CloudFormation, BigQuery performance tuning, cost optimisation, DBT Cloud governance, Airflow workflow optimisation, monitoring, Cross-cloud pipelines, data movement, AWS, GCP, Security, IAM, data-access design, regulated financial services environments
What You'll Do.
Design data pipelines
Operate data pipelines
Orchestrate data workflows
Automate data workflows
Perform DBT transformations
Implement testing frameworks
Manage environment governance
Deploy Infrastructure as Code
Optimise pipeline performance
Optimise SQL performance
Optimise BigQuery performance
Optimise AWS data services performance
Create technical documentation
Provide production support
Handover to internal teams
How You'll Work.
Team & Collaboration
Collaborate with cross-functional stakeholders; Collaborate with analytics; Collaborate with product; Collaborate with platform engineering; Collaborate effectively in multi-disciplinary teams
Communication Scope
communication skills; stakeholder management skills
Process & Methodology
Agile delivery frameworks, JIRA, Confluence, delivery management
Full Job Description
Technology is our how. And people are our why. For over two decades, we have been harnessing technology to drive meaningful change. By combining world-class engineering, industry expertise and a people-centric mindset, we consult and partner with leading brands from various industries to create dynamic platforms and intelligent digital experiences that drive innovation and transform businesses. From prototype to real-world impact - be part of a global shift by doing work that matters. Role Overview and Expected Deliverables The engineer will design, build and operate scalable, secure and analytics‑ready data pipelines and models across GCP BigQuery and AWS, delivering: - Airflow‑orchestrated data workflows and automations. - DBT Cloud transformations, testing frameworks and environment governance. - Robust CI/CD and Infrastructure as Code (IaC) deployments (GitHub Actions, Bitbucket, Bamboo, Terraform or CloudFormation). - Performance optimisation across data pipelines, SQL, BigQuery and AWS data services. - High‑quality technical documentation, production support, incident response and handover to internal teams. - Close collaboration with cross‑functional stakeholders including analytics, product and platform engineering. ## Qualifications Must have skills GCP, BigQuery, Cloud Storage, Apache Airflow, dbt, Python, SQL, data pipelines, ingestion, transformation, Git/Bitbucket, data quality checks Good to have skills Dataplex, Collibra integration, CI/CD, Grafana, Splunk, Power BI data preparation, financial services data Core Technical Requirements Cloud & Platform Engineering: - Strong proficiency across AWS and GCP. - On AWS: IAM roles and policies, Lambda, S3, RDS, Redshift. - On GCP: BigQuery, workload optimisation, cost management. Data Engineering Tooling: - Hands‑on experience building data pipelines for data warehouse environments. - Strong SQL capability including analytical and window functions. - Advanced dbt Cloud experience (models, SCDs, tests, macros
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