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Data Strategy: Requires knowledge of understanding of business value and relevance of data and data enabled insights / decisions; Appropriate application and understanding of data ecosystem including Data Management, Data Quality Standards and Data Governance, Accessibility, Storage and Scalability etc; Understanding of the methods and applications that unlock the monetary value of data assets.
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5 years of experience must include: Data analytics and statistical analysis of financial risk data; Policy and regulatory analysis; Data analytics tools including: R, Excel, and PL/SQL; Anti-Money Laundering (AML) and Know Your Client (KYC) guidelines; Oracle and relational databases; and User Acceptance Testing (UAT) and defect management.
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Using the Cloud OTI Data Platform, the Senior Data Engineer will build highly available, robust, concrete data pipelines and reporting solutions following industry best practices, adhering to OTI security guidelines, modifying, and running automated CI/CD pipelines used for releasing code, and modifying and executing terraform modules for deploying infrastructure components, working collaboratively under the direction of OTI data engineering management and leads.
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Understanding of SOA, Data integration, Data Quality, data architecture and Master Data Management, project life cycle Phases, best practices and processes. Must have good understanding of Master Data Management (MDM) architectures and business processes.
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Key areas of focus include cybersecurity, data privacy, health and safety, physical security and anti-bribery and corruption. You will be responsible for developing and managing their Americas Region enterprise risk management program for their Real Estate assets.
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You can translate investigative capabilities into effective automation, instrumentation, and tooling, based on an understanding of how analysts need to synthesize disparate sets of data from sources such as malware, cyber attack patterns, and closed and open-source intelligence.
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The ideal candidate will have a strong background in data operations, with specific expertise in Snowflake and cloud-based data warehousing technologies along with proficiency in JIRA or similar project management tools.
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Experience in management and tuning of data platforms like Azure ADLS storage and Databricks. Mandatory Skills : Azure Databricks, Azure data lake , Ansible, SQL, Terraform, Snowflake, Kafka , Azure CLI, Databricks CLI, PowerShell and/or Bash.
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At least 2 years of experience in information technology (operations, software delivery, access management, microservices), information security (application security, network security, cyber security, data protection), information systems risk management, information systems auditing, or a combination.
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Experience with modern data engineering tools such as Talend, DBT, Databricks, Snowflake and data visualization tools such as PowerBI, Tableau, ThoughtSpot. Deep understanding and proven experience in Databricks, Azure Data Factory, Synapse.
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Experience with configuration / management of Microsoft Power BI Service Experience extracting, manipulating and analyzing data via Dataflows, Datamarts, Dashboards and Apps to recommend and/or take action.
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Experience in design and development of large-scale data solutions using GCP services like DataProc, Dataflow, Cloud Bigtable, BigQuery, Cloud SQL, Pub/Sub, Cloud Data Fusion, Cloud Composer, Cloud Functions, Cloud storage, Compute Engine, Looker and Cloud IAM.
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Including hands on experience with productionized data ingestion and processing pipelines using T-SQL, SSIS, Python, Data bricks, Snow SQL. Minimum 5 years of designing and implementing an operational production grade large-scale data solution on Microsoft Azure Snowflake Data Warehouse.
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Utilizing knowledge of Snowflake to offer insight into data warehousing and management. Ensuring data security and compliance in Databricks and Snowflake environments. Solid experience in Databricks platform, data engineering, and using Delta Live Tables.
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Asset Management: IPV Curator, SGL/FlashNet, Storage DNA, Spectra Logic, and Metadata management and validation. Define and lead all policies, procedures, and workflows for the Media Asset Management (MAM) system and video asset lifecycle, from acquisition through ingest and archive, post-production, distribution, and retention.
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tiger data management jobs in Jersey City, NJ
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