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Responsibilities:Work as part of a team to develop Cloud Data and Analytics solutionsParticipate in development of cloud data warehouses, data as a service, business intelligence solutionsAbility to provide solutions that are forward-thinking in data and analytics'Deliver a quality product, Coding complex U-SQL, Spark (Scala or Python), T-SQLDeveloping Modern Data Warehouse solutions using zure Stack ( zure Data Lake, zure Data Factory, zure Databricks.
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Database / Warehouse: PostgreSQL, DynamoDB, Databricks Unity Catalog. Direct hands on experience with highly scalable data pipelines using BigData technologies (Spark, Hive, Airflow, DBT, Parquet / ORC, Kafka / Streaming, etc.
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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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4+ years using cloud-based warehouse/data lake (Preferably in Azure Databricks metastores/catalogs or similar stacks such as AWS Athena/Redshift, GCP Bigquery, Azure ADLS, etc) Supporting the data organization through Azure Databricks admin tasks.
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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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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. Implement data engineering, ingestion, and curation functions on Azure cloud using Azure native programming.
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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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Tools to secure the data within your purview (e.g., Redgate Catalogue, Masking and Cloning) 5+ years of experience in data software development building data platforms for batch or streaming ingestion, processing the data for analytics, and storing the data in various stages.
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Advanced experience in SQL in big data warehouse systems such as Snowflake, BigQuery, Databricks, etc. 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.
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3+ years of Experience with specialized data architecture (e.g., data lake, lake house, data fabric, data mesh, optimizing physical layout for access patterns) Operationalize large-scale enterprise data solutions and applications using Azure data and analytics services.
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Participate in provisioning data storage services, transforming data and implementing security requirements. Integrate, transform, and consolidate data from both structured and unstructured systems into a structure that is suitable for building analytics solutions.
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Designing, building and maintaining data ETL/ELT pipelines to source and aggregate the required data for various data analyses and reporting needs, as well as to continually improve the operations, monitoring and performance of the data warehouse.
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Creates Infrastructure as Code (IaC) scripts (Bash, JSON, YAML, Terraform, CloudFormation) 2+ years of hands-on development experience with event based streaming technologies (Apache Kafka / Azure Event Hub or similar.
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Experience managing databases, Azure Data Platform services (Azure Data Lake (ADLS), Data factory (ADF), Data Lake Analytics, Stream Analytics, Azure SQL DW, HDInsight/Databricks, NoSQL DB), SQL Server, Oracle, Data Warehouse etc.
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Leverage DevOps techniques and practices like Continuous Integration, Continuous Deployment, Test Automation, Build Automation and Test-Driven Development to enable rapid deployment of end user capabilities.
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