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3+ years of experience with Big Data tools/technologies like Hadoop, Spark, Spark SQL, Kafka, Sqoop, Hive, S3, HDFS, or. Our client is currently seeking an experienced Data Engineer – Big Data individual for their Midtown office in Atlanta, GA. The successful candidate must have Big Data engineering experience and must demonstrate an affinity for working with others to create successful solutions.
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Proficiency with data warehouses (e.g., Snowflake, SQL Server, Redshift, Big Query etc.) The Lead Cloud Engineer will help our data engineering initiatives with a particular focus on leveraging AWS, GCP, Snowflake, SQL Server, Oracle, Python, Apache Airflow, SSIS, and DataStage.
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Platforms: Experience with big data technologies like Synapse Analytics, Microsoft Fabric, Hadoop/hive, Greenplum, and Databricks etc. Strong understanding of big data technologies such as Synapse Analytics, Microsoft Fabric, Hadoop/hive, Greenplum, and Databricks etc.
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Exceptional Microsoft SQL Server design and development skills Service Development: RESTful APIs, Microservices, ASP.Net Core, Azure API Management, Azure API Apps Data: Microsoft SQL Server, Azure SQL, Entity Framework/CosmosDB, MongoDB (nice to have) Strong JavaScript framework experience with React.
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Technical Skills: Experience working with a wide variety of technologies, including: Electronic Medical Records, and Electronic Health Record systems (EMR, EHR) Database technologies (SQL, NoSQL, Oracle, MySQL) Big data technologies (Hadoop, Spark) Data visualization tools (Tableau, Power BI, Cogito) DevOps tools (Azure, Docker, Kubernetes, Jenkins) Enterprise systems (ERP, CRM) Familiarity with healthcare data standards and interoperability.
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Experience with multiple information technology and security technologies: IIS, SQL, firewall, IPS/IDS, Windows, Linux, Anti-Virus, mail filtering, WAF, encryption, CA authority, IDM/IAM, multi factor authentication, SSO, VPN, Zero Trust Technologies, Vulnerability Management, DDoS, SIEM, FIM, WIPS, MDM, Pen Testing, VMware and VM server platforms.
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Minimum of 3 years using at least one ETL tool such as Microsoft SQL Server Integration Services (SSIS), AWS Glue, Microsoft Azure Data Factory, IBM Infosphere DataStage, or any ETL applications.
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We still have a legacy data landscape involving both MS SQL Server and Oracle databases. You will have indepth knowledge and experience in; cloud data lake house; Databricks (preferred) or Snowflake; cloud-native solutions knowledge; SQL or Python; modern DevOps approach; have written data code AND also the CI/CD pipelines.
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Pilot a new tool (either something you helped build in SQL, Python, Go, or other languages, or a modern data stack tool from an open-source project or a third-party vendor) to help improve the automation and reliability of our data processing infrastructure.
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1+ years professional experience with SAS, SQL, R, Python or other statistical programming language (SAS/SQL preferred) (Mid Level) 3+ years professional experience with SAS, SQL, R, Python or other statistical programming language (SAS/SQL preferred) (Senior.
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Apply machine learning, econometrics/statistics, predictive modeling, return-on-investment analysis, simulation, and data visualization methods to support the development of health policy. The Payment Model Implementation Analytics Consultant will provide support on a number of payment model implementation contracts requiring intermediate SAS, R, Python, or SQL experience as well as knowledge of statistics and research methodology.
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Responsibilities: · Responsible for the administration, configuration, and optimization of the Databricks platform to enable data analytics, machine learning, and data engineering activities within the organization.
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Solid experience with architecting and implementing metadata management including data catalogues, data lineage, data quality and data observability for big data workflows.
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The purpose of the Analyst, Predictive Modeling position is to analyze data to drive better business decisions, including: Pricing and credit risk, loan servicing strategies, business policies, processes, and performance, and champion/challenger tests.
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Experience working with big data technologies (Spark, Hadoop) Work with modern tools such as Snowflake, Databricks, Fivetran, and dbt, and write code in SQL, Python, and Spark. Experience working with cloud data warehouses (Snowflake, Google BigQuery, AWS Redshift, Microsoft Synapse.
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big data sql server jobs Title: manager in Atlanta, HI, Canada
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