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Work with a team with respect to discovery, design and delivery of data models, data governance models, data migration plans, data warehouse design and reporting components of applications using GCP, Databricks and Microsoft tools.
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As a member of the Data Engineering Blockchain team, you own the ETL/ELT pipelines and data warehouse that are used to analyze trends and activity on the blockchain. Advanced experience in SQL in big data warehouse systems such as Snowflake, BigQuery, Databricks, etc.
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What you’ll be responsible for:As a member of the Data Engineering - Business ETL team, you own the ETL/ELT pipelines and data warehouse that is used for financial and regulatory reporting.
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Understanding of enterprise data management concepts (Data Governance, Data Engineering, Data Science, Data Lake, Data Warehouse, Data Sharing, Data Applications.
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Working closely across groups, such as the product, engineering, data science, and external partners for data modeling, general management of data life cycle, data governance and processes for meeting regulatory and legal requirements.
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As a member of the Data Engineering - Business ETL team, you own the data warehouse and data pipelines that are used for financial and regulatory reporting. 4+ years of professional data engineering experience.
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Exp designing and delivering data engineering solutions with Databricks Exp in Azure Databricks Experience in Data Engineer in zure Big Data Environment Expertise in ETL tools i.e. (Infomatica, Talend, SSIS, Data Stage) Expertise in Implementing Data Warehousing Solutions Exp with working in Agile (KANBAN, Scrumban) environment Exp in zure stack ( zure Data Lake, zure Data Factory) Exp in Scala or Python, T-SQL.
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8+ years of professional data engineering or software engineering experience, with a focus on heterogeneous, large-scale data processing for machine learning pipelines. Stay up to date with emerging technologies, best practices, and industry trends in data engineering and software development.
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Experience implementing and maintaining data platform core services (data lake, data integration, data warehouse) and configuring and integrating infrastructure and PAAS (e.g., Azure Data factory, Informatica cloud services, Databricks, Data gateway and Qlik Sense, Power BI.
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Implement data engineering, ingestion, and curation functions on Azure cloud using Azure native programming. Hands-on experience working with Azures PaaS offerings such as Purview, Databricks, Azure Data Lake Storage, Data Factory as well as monitoring of the environments.
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As a Senior Data Platform Engineer on the MMA IT Data and Analytics Team, we will count on you to design, monitor, build, and automate data pipelines. Learn more about what makes us different and how you can thrive as a Senior Data Platform Engineer at MMA.Marsh McLennan Agency (MMA) provides business insurance, employee health & benefits, retirement, and private client insurance solutions to organizations and individuals seeking limitless possibilities.
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Be familiar with our current data warehouse and data models, know where to find business critical data and provide requirements to the product and data engineering teams.
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This role will provide expertise to support the development of a Big Data / Data Lake system architecture that supports enterprise data operations for the District of Columbia government, including the Internet of Things (IoT) / Smart City projects, enterprise data warehouse, the open data portal, and data science applications.
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At least two years experience in implementing, automating and integrating Big Data infrastructure resources like S3, Redshift, Aurora, Kinesis, Kafka, EMR, Lambda, SNS, Azure Blob Storage Account ,SQL Data Warehouse, Microsoft Event Hubs , HDInsights, Azure Databricks, Azure Functions,Event Grid, Data Lake Analytics in an ephemeral/transient and in an elastic manner.
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Design and implement cloud-based solutions using Microsoft Fabric technology stack and Microsoft SQL Server, including Azure Synapse Data Engineering, Azure Data Factory, Synapse Data Science, Synapse Data Warehouse, Synapse Real-Time Analytics, Onelake, and Power BI, with a focus on data migration, movement, and transformation.
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