Assurant is looking for a Data Engineer to construct, test and maintain scalable data solutions for structured and unstructured data to support their reporting, analytics, ML and AI solutions. The Data Engineer will contribute to the design, development of data-pipelines and feature engineering of data solutions.
Duties and Responsibilities
- Gains a thorough understanding of the requirements and ensure that work product aligns with customer requirements.
- Works within the established development guidelines, standards, methodologies, and naming conventions.
- Builds processes to ingest, process and store massive amount of data.
- Assists with optimization and performance of bigdata ecosystems.
- Performs productionization of Machine Learning and Statistical models for Data Scientists & Statisticians.
- Assists with research and building of proof of concepts to test out theories recommended by Senior and Lead Data Engineers.
- Collaborates and contributes in identifying project risks, design mitigation plans, develops estimates.
Ideal Candidate/Basic Qualifications
- Bachelor of Science in Computer Science or in a related field required.
- 5 years of design, development and production support experience on Data Warehousing and Business Intelligence.
- 5 years of experience with SQL Server, C#/.NET using On-Premise and/or Microsoft Cloud Service Models: PaaS, IaaS, SaaS.
- Experience using Azure offerings for Compute, Containers, Big Data, Data Analytics : Data Lake, Data Factory, Stream Analytics, NoSQL.
- Expertise with scripting languages like Python (or similar) , Linux shell or Windows Power-shell and/or Azure CLI.
- Ability to use and create web services and other integration technologies (REST, XML/JSON, SOAP).
Preferred Experience, Skill and Knowledge
- Knowledge in fundamentals of Machine Learning and Artificial Intelligence using Microsoft technologies.
- Experience with Azure Databricks, HDInsight, Spark, Hadoop is highly desirable.
- Data profiling and dimension modeling techniques and creation of logical and physical data models.
- Experience working with job scheduling tools.