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Reporting to the Data Management Director, US Region; the Data Operations Lead is a key member of the team. Lead a small team on day to day operations for Data Quality, data bug investigations, and source to target reconciliation.
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Google Data Analytics Professional Certificate, Power BI Data Analyst Associate, AWS Certified Data Analytics, Enterprise Data Warehouse certifications, Palantir, Client Side performance metrics tools e.g. Quantum Metrics.
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Propose new database architecture and support data migration from an existing Legacy system to a new structureCreate source-to-target mapping documents to transform the source data into the target warehouse and test final transformations.
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3+ years of experience in batch and streaming ETL using Spark, Python, Scala, Snowflake, or Databricks for Data Engineering or Machine Learning workloads. Enable data discovery and curation for analytical purposes by collaborating with data scientists and providing data integration solutions.
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Our integrated platform combines continuous spend monitoring of data from systems like SAP, Oracle, and Concur with workflow automation tools to help global organizations prevent and detect fraud, corruption, conflicts of interest, and other economic crimes.
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Regulatory Compliance: Familiarity with relevant regulations and guidelines governing credit data, such as CCAR, CECL, and Basel III. Develop and Implement Data Strategies: Create and execute data strategies to support credit risk management, ensuring alignment with the bank's overall risk management framework.
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Keep pulse of the latest development trends in cloud (AWS, GCP, Azure, etc), data platforms (Databricks, Snowflake etc), databases (RDBMS, SQL, NoSQL, Oracle, etc.) Understanding of streaming (e.g. Kafka, Kinesis), batch & workflow (e.g. Airflow, AWS Glue, CTTRL-M) data transport technologies.
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Knowledge of Statistics, Gen AI, LLM, Python, Computer Vision, data visualization tools. We want Data Science/Machine Learning/Data Analyst and Java Full Stack candidates. Currently, we are looking for entry-level software programmers, Java full-stack developers, Python/Java developers, data analysts, data scientists, and machine learning engineers for full-time positions with clients.
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As a Quant Data Engineer, you'll collaborate closely with various departments within the organization and your primary responsibility will involve constructing and maintaining data ingestion processes of varying complexity that drive investment decisions and support critical operations.
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Data : Apache Spark, Kafka, Redshift, Snowflake. As the Delivery Manager, you will be responsible for overseeing the successful delivery of complex technology projects with a focus on AWS, DevOps, Data Engineering, and Generative AI solutions.
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Technicians will learn and gain experience through assisting more experienced data center technicians in day to day operations of the data center including security functions, general site response and triage, and customer interaction.
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WHAT YOU’LL DO Lead and contribute hands-on to major data engineering initiatives from inception to delivery. Experience with Data Ops (VPCs, cluster management, permissions, Databricks configurations, Terraform) in Cloud Computing environments (e.g., AWS, Azure, GCP) and associated cloud data platforms, cloud data warehouse technologies (Snowflake/Redshift), and Advanced Analytical platforms (e.g., Dataiku and Databricks.
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Experience building and managing production-grade data pipelines using tools such as Airflow, dbt, DataHub, MLFlow. Youll be part of a close-knit team of data engineers developing and maintaining a data platform built with automation and self-service in mind to support analytics and machine learning data products for the next generation of our T3 Fleet that enable end-users to track, monitor and manage the health of their connected vehicles and deployed assets.
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Lead and manage the data engineering team, including hiring, onboarding, performance management, career development, and retention. We are looking for a Senior Data Engineering Manager to lead our data engineering team and oversee the development and implementation of technical solutions for our data platforms.
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Agility core practices, Analytical Thinking, Computational Thinking, Continued Learning, Data Analysis, Data cleansing and transformation, Data Management, Data Sourcing, Data visualization and interpretation, Dialogue enablement, Exposure Management, Machine Learning, Macroeconomics, Market analysis methods, Market Risk Management, Statistics, Trade execution and management, Trading Fundamentals, Sentiment and Trends, Trading knowledge.
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data job Title: operations lead Company: Toast in Chicago, IL
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