Azure Data Engineer with Insurance P&C Exp

As a Lead Data Engineer, you will be expected to provide expert level data solutions by using software to process, store, and provision quality data. Responsible for leading, instructing and mentoring a team of data engineers and are expected to have the oversight of all deliverables to ensure the designed data pipelines are scalable, repeatable, and secure. Note: Candidate should be ready for short term travel to NY/NJ client location for KT Responsibilities: Leads all phases of solution development. Designs and codes complex ETL (Extract / Transform / Load) processes and adhoc queries. Ensures that all code is well structured, includes sufficient documentation, and is easy to maintain and reuse. Integrates complex and large scale data from a variety of sources for business partners to generate insight and make decisions. Must be a forward thinker that sees the larger picture; looks beyond the current, anticipates what could happen or what the future needs will be. Translates business specifications into design specifications and code. Assesses data quality and tests code thoroughly for accuracy of intended purpose. Educates and mentors team of data engineers on the team while applying quality control to their work. Develops data engineering standards. Troubleshoots software and processes for data consistency and integrity. Experience: Expert level Data Engineer with solution architecture experience Well-seasoned in data modeling, data intake, and data-curation procedures Experience as Data Engineer In-depth practical experience and demonstrated comprehensive know-how in designing and implementing modern cloud architectures based on micro-services and continuous delivery Proven experience in software development projects with Java Spring, Docker, Git, Maven/Gradle and/or Jenkins Outstanding SQL and Java skills, proven project experience in setting up structured and unstructured data stores (e.g. SQL Server, Oracle, HIVE, HBase, HDFS, Neo4J, MongoDb, etc.) and streaming solutions (e.g. with Kafka, Spark, Storm, Flink or MQTT) Experience with agile methods such as SCRUM, Design Thinking Experience with data protection regulations (e.g. GDPR), data masking techniques and the concepts of k-anonymity and i-diversity Ability to develop a holistic approach and to abstract reasoning, as well as the ability to communicate complex issues to internal and external non-professionals in an easily understandable way Strong service orientation, target driven, high degree of intercultural competence, team player with highest commitment Strong leadership and interpersonal skills Ability to schedule and prioritize workload demands on a team Excellent understanding of (re-)insurance processes, business models (incl. new digital services), systems and data