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Demonstrated work experience with Cloud: Distributed Scalable Big Data Store (NoSQL) such as CloudBase/Accumulo, Big Table; MapReduce and technologies such as Hadoop, Pig, HDFS; Serialization such as JSON or BSON.
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We are looking for a senior data solutions engineer with extensive experience in the big data and data warehouse ecosystems. In addition, be a key contributor in delivering critical business features with a passion for big data technologies.
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Proficiency in data technologies, such as relational databases, data warehousing, big data platforms (e.g., Hadoop, Spark), data streaming (e.g., Kafka), and cloud services (e.g., AWS, GCP, Azure.
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Big Data Analytical 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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Experience using big data technologies (Snowflake, Airflow, Kubernetes, Docker, Helm, Spark, pySpark) Research and evaluate new technologies in the big data space to guide our continuous improvement.
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Familiarity with information technology, business processes and financial reporting audits and familiarity with control frameworks such as NIST, MITRE ATT&CK, COBIT, ITIL, PCI, ISO, SOX, and global data privacy laws (e.g., GDPR, CCPA.
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Sound knowledge on Snowflake, Databricks, Informatica and other leading Data Products. Preferred Qualifications: Knowledge in enterprise data management architecture and principles, master data management, data governance and data qualityKnowledge in data modernization, Cloud, data migration and digital transformationMBA or master’s degree experience from a top-ranked institution.
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Experience designing and building highly available, distributed systems of data extraction, ingestion, normalization and processing of large data sets in real time as well as batch, that will be used across engineering teams using orchestration frameworks like Airflow, KubeFlow or other pipeline tools.
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Previous data entry experience working in QuickBooks and other Intuit platforms, Salesforce, and Wrike is strongly preferred. This detail-oriented role requires excellent data entry, technology, and communication skills.
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Big Data Machine Learning Engineer. The Big Data ML Engineer fills a critical data, analytics, technology support, and innovation role for the business analytics and advanced analytics functions within the organization.
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Implement data processing pipelines using Azure Data Factory, Databricks, Azure Machine Learning, Azure Logic Apps, Azure Function Apps, Azure Kubernetes container and other big data services.
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We are looking for a Vice President, Analytics & Insights to derive and deliver data-driven, actionable insights to answer client business challenges while also demonstrating the business impact of our work.
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Advanced experience in SQL in big data warehouse systems such as Snowflake, BigQuery, Databricks, etc. Internal knowledge of open source or related big data technologies. What you’ll be responsible for: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.
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Intermediate (3+ years) experience building database models for data visualization tools such as Power BI, Sigma, Tableau, or Looker. Hands-on experience building data warehouses and data marts with cloud databases such as Snowflake, Redshift, Oracle ADW, Azure SQL Server.
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Data backup and recovery solutions (Datto, Code42, AWS Glacier, etc) Apple MDM (Jamf, Addigy) experience is a big plus. You have previously worked with MSP tools such as Beyond Identity, Okta, HaloPSA, NinjaRMM, Liongard, Auvik, Jira, Cato, Crowdstrike, Intune, MS Graph API, Hudu, PagerDuty, Rewst, Slack, etc.
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big data jobs Title: data administrator Company: Cognizant Technology Solutions in Chicago, IL
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