Citizen Event Analytics (CEA) is a cross‑benefit, cross‑channel event history compiled from citizens' interaction (telephony, face‑to‑face and digital), claim processing and support events.
CEA uses a pipeline that extracts, transforms, and loads event data from different sources into the Uplifted Analytical Service (UAS) data asset.
Responsibilities
* Plan and lead development on sets of related stories.
* Understand the overall CEA system and teach it to others.
* Collaborate with other users, Product Owner and Business Analyst to understand what needs to be built.
* Coach and mentor more junior colleagues.
* Operate ingest and publishing production pipelines/services, improve system robustness, resilience and stability.
* Support DWP in the maintenance of the longitudinal event history data asset and associated data pipelines.
Key Skills Required
* Understanding of data processing using Apache Spark.
* Use of Python, SQL, and familiarity with PySpark.
* Experience using Apache Airflow for task orchestration.
* Understanding of EMR and reviewing output logs.
* Use of Jupyter notebooks and/or Amazon Athena to query and validate data.
* Data analysis to identify root cause of issues.
* Understanding of dimensional data models and slowly changing dimensions/historic data capture.
* Use of AWS console and services such as CloudWatch, IAM, S3, Glue, ECR, EC2, EMR, DynamoDB, LakeFormation.
* Familiarity with Amazon Textract and Comprehend.
* Understanding of both server‑side and client‑side encryption.
* Use of GitLab for source code management, pipelines for CI/CD, release tagging and deployments.
* Use of GitLab Tags for component versioning in shared repositories.
* Understanding of Docker and containerization of solutions.
* Infrastructure as Code using Terraform.
* Experience of understanding how customer expectations transition to applied functionality.
* Familiarity with DWP Engineering best practices.
* Familiarity with basic data structures for constructing a solution.
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