Company 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.
Job Description
Our data team has expertise across engineering, analysis, architecture, modeling, machine learning, artificial intelligence, and data science. This discipline is responsible for transforming raw data into actionable insights, building robust data infrastructures, and enabling data-driven decision-making and innovation through advanced analytics and predictive modeling.
As a [job title] at Endava...[enter 2-3+ sentences here describing the core responsibilities and expectations of the role] Responsibilities:
Working with Endava’s customers to analyze existing systems and prepare plan for migrating databases and data processing systems to cloud
Defining and implementing cloud data strategy including security posture, target operating model, DR strategy and others
Deliver end-to-end data solution – from early concept and planning, through early Po Cs and benefits analysis, all the way to production roll outs.
Enhance client’s data landscape by improving data lineage, quality and reliability
Help organizations adopt AI/ML based solutions by introducing MLOps culture
Be part of technical advisory and cloud infrastructure team responsible for
Secure foundational Data Lakes and Data Meshes implementations
Automated provisioning of infrastructure and pipelines
Cloud-ready ETL/ELT architectures
Presenting analytical findings on cutting-edge BI Dashboards
Qualifications
Understanding of entire software development lifecycle, CI & CD as well as Data/MLOps approach
Expert knowledge of SQL and at least one language used in Data Analytics/Science space (Python, R, SAS)
Knowledge of at least one programming language (Java, C#, C++)
Knowledge of Big Data and Orchestration tools such as Apache Airflow or Spark
Experience working with Relational and No SQL databases
Working experience with BI Tools (Looker, Power BI, Tableau, Data Studio)
Basin understanding of GIT various automation servers (Jenkins, Circle CI, Git Lab CI)
Knowledge of messaging systems
Basic Knowledge of containers, Docker and Kubernetes
Cloud certifications such as Associate Cloud Engineer will be an asset
Additional Information
Discover some of the global benefits that empower our people to become the best version of themselves:
Career Development: Career coaching, global career opportunities, non-linear career paths, internal development programmes for management and technical leadership;