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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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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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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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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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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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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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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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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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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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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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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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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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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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Find even more open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general - ordered by popularity of job title or skills, toolset and products used - below.
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As a Data Scientist at Capital One, you ll be part of a team that s leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.
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big data jobs Title: developer Company: Cognizant in Chicago, IL
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