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3+ years of experience with distributed data/computing tools (MapReduce, Hadoop, Hive, EMR, Kafka, Spark, Gurobi, or MySQL) The Machine Learning Experience (MLX) team supports an internally hosted Model Training ecosystem running critical infrastructure for machine learning and data analysis across Capital One. You will get an opportunity to collaborate on the 1000's of models being trained on the platform by 4000+ users and dive deep into the unique engineering challenges we have around compute, data access, security and scale.
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Good appreciation and at least one implementation experience on processing substrates in Data Engineering - such as ETL Tools, Kafka, ELT techniques. Strong knowledge of cloud native data platform architectures, data engineering and data management.
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Software Engineering ManagerDescription -ACS (Advanced Compute & Solutions) is seeking a Software Engineering Manager to lead ACS Software Development in our high growth, future-oriented businesses, including Data Science, AI and other emerging areas.
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We are seeking an experienced Software Engineering Manager I, driven and empathetic, to lead our APM Telemetry & Analytics Team. This role is perfect for those passionate about data-driven decision-making and adept at leading teams to technical and operational excellence.
$187,000 - $240,000 a yearFull-timeExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
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Hands-on experience in Talend data pipelines around event and messaging patterns, streaming data, Kafka , API. Ability to provide technical guidance to data engineering team for Talend pipeline design and enhancements.
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Implement data engineering, ingestion, and curation functions on Azure cloud using Azure native programming. Experience implementing and maintaining data platform core services (data lake, data integration, data warehouse) and configuring and integrating infrastructure and PAAS (e.g., Azure Data factory, Informatica cloud services, Databricks, Data gateway and Qlik Sense, Power BI.
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Must have: 6 years of experience in data engineering Experience with Extract, Transform and Load (ETL) tools and processes Experience with Python Bash / shell scripting Linux Familiarity with different data types & formats, including text, audio, imagery, video, binary and geopspatial.
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Dayton, OH is highly focused on the Space-based mission set with a heavy emphasis on sensor exploitation and analysis; Tampa, FL focuses on ‘art-of-the-possible’ analytics of all kinds with an emphasis on graph technologies, NLP, and wrangling complex data sets; and all forces converge at our headquarters in the Northern Virginia/Washington DC area where we host our tech events and support engineering and analytic missions across several IC and DOD agencies.
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Master of components necessary to architect solutions for complex data platforms, and large scale CI/CD data pipelines using a variety of technologies (REST APIs, Advanced SQL, Amazon S3, Apache Kafka, Data-Lakes, etc.
Full-timeExpandApply NowActive JobUpdated 8 days ago - UpvoteDownvoteShare Job
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Designing and implementing Distributed systems like Spark, Kafka and leveraging Data Container Orchestration services including Docker and Kubernetes, and a variety of AWS tools and services.
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Must have hands-on expertise in Cloud Computing (Azure, AWS), Big Data Processing using Oracle, Hadoop/HBase/Kafka/Spark of Data PlatformsMust have strong technical knowledge, wide range application architectural, development and database technologies, tools, Hive, Spark SQL and Spark with Python, Java etc.
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Minimum 3 years of experience in building and managing high-performing teams in a remote setup, with a focus on operating large-scale data pipelines leveraging technologies such as Scala, Spark, ML, Protocol Buffers, Kafka, Airflow and Elasticsearch.
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Our Principal Engineer is a lead member of the engineering staff working across Business Services Engineering, Data Engineering, Platform Engineering, and Infrastructure Engineering to ensure that we provide a friction-less experience to our customers, maintain the highest standards of protection and availability.
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Experience with big data technologies such as Hadoop, Spark, or Kafka. Stay up-to-date with emerging technologies and industry trends in data engineering and cloud computing.
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Ensure data security and governance standards are implemented across the Kafka platforms. 6+ years of hands-on software engineering experience with Java and building Kafka applications.
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