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The Sr. Manager, Software Engineering will report to the Director of Technology. Experience with cloud infrastructure technologies with AWS, Azure, and Google Cloud Provider.
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Hands-on experience with big data technologies and cloud (Databricks / Spark, Azure/AWS/GCP). If the candidate does not have a background in Actuarial science, the candidate should have 4+ years of industry experience building and analyzing machine learning models and should hold a graduate degree in a technical field such as Statistics, Computer Science, Data Science, Bioinformatics, Physics, Mathematics, Economics or Engineering.
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Experience with at least one major Massively Parallel Processing (MPP) or cloud database technology (Snowflake, Redshift, Big Query) Expanding, scaling, and standardizing the core foundational principles through consistent observability, lineage, data quality, logging, and alerting across all engineering teams in the Data organization is imperative to the creation of a single pane of glass.
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DE performing full stack development in an Information Technology (IT) product development organization, and Amazon Web Services (AWS) environment, using TypeScript, Node.js, Java, API development, Spring Boot, Apache Tomcat, and RDBMS; and analyzing, designing, developing, and testing scalable Cloud based software applications.
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Architect, design, develop and maintain data engineering solutions primarily utilizing Python, SQL and Apache Spark based platforms. Experience with Big Data platforms such as Databricks is a plus.
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2 or more professional certifications (SAFe PM/PO, Security+, CCSP, CISA, CRISC, AWS Cloud Practitioner, CISSP) Contribute to the development of a healthy product backlog, collaborating with the Product Manager, Engineering, and Solution Architects to break down business epics, document user stories (to also include things like addressing technical debt, SRE, etc.
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Job Schedulers – Airflow, Oozie or other ETL Scheduler Data Analytics – AWS Cloud Native Services Big data architecture – Python, Scala, Hadoop Bigdata, Hive, Pyspark etc.
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Department Summary: The Data Environments and Engineering Department (L146) in the Data and Human Centered Solutions Innovation Center is seeking highly motivated, adaptive, and enthusiastic candidates with a wide variety of interests and a foundation of skills in systems engineering, software engineering, information systems, or data engineering to join our department as a Senior Data Engineer.
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Data governance,Data quality,Reporting,Governance risk and compliance grc software. Data governance, Data quality, Reporting, Governance risk and compliance grc software.
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Production experience in log onboarding to logging platforms to support SIEM and ObservabilityPractical experience with Data Engineering for CIM complianceExtensive experience building large scale distributed systems and data analytics processes on cloud native, in-memory, and fit-for-purpose hybrid infrastructure.
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Key responsibilities for the Senior Software Engineer, UX Engineering include:Lead the development, deployment, and maintenance of full-stack, data-driven, cloud applications that serve our scientific community.
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Must have Master's degree or foreign equivalent in Computer Science, Computer Engineering, Electronic Engineering, or a related field and 2 years experience in the proffered position, or as a Developer, Software Engineer, Technology Analyst, Programmer Analyst, or related occupation.
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Proven expertise in Azure/AWS cloud services and cloud-native architecture, with a strong ability to guide and mentor teams in leveraging these technologies. Drive a long-term vision to scale engineering processes, infrastructure, and technology stacks to support organizational growth and evolving business needs.
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Establish strong software engineering principles for development in Python on the Azure/Google Cloud Platform. Experience with Snowflake/BigQuery, Google Dataproc/Databricks or any big data frameworks on Spark.
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Big Data & Streaming: 2+ years using big data and/or streaming technologies (e.g. Apache Spark, Apache Kafka, Apache Flink) Cloud: Experience building with and deploying to cloud platforms such as AWS and leveraging serverless architectures (e.g. Lambda, Glue.
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