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Python, Apache Airflow, Apache Spark, PostgreSQL, Presto SQL, Snowflake SQLAmazon Web Services (Security Groups, Batch, Lambda, SSH, S3, ECS, EC2, ALB, RDS, IAM, SNS, Fargate, ElastiCache, Redis.
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The leader we hire will build a versatile team skilled in secure and scalable ML infrastructure on industry standard frameworks like Jupyter notebooks, Apache Spark/Flink on K8s, Tensor flow, Theano, Caffe, or PyTorch for efficient model lifecycle, training and inferencing pipelines, scalable feature stores, online and offline graph datastores; and transition us from the current state of monolithic architectures to a modern AIML stack.
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Experience with data engineering tools and languages such as Apache Spark, Python, Java, and Scala. Experience setting up operations and pipelines for new and existing projects and/or familiarity with version control (i.e., Git, GitHub), CI/CD tooling (e.g., Azure DevOps Pipelines artifact repositories (e.g., Azure Container Registry, JFrog Artifactory), monitoring tools (e.g., Grafana, Prometheus), model monitoring tools (e.g. Weights & Biases, mlflow), and associated process automation (e.g. Apache Airflow.
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Required Skills: Python, MWAA (Airflow), Spark Optimization, AWS Glue, AWS EC2, Apache Spark. The ideal candidate will contribute to our Asset & Wealth Management domain leveraging their expertise in Python Apache Spark and various AWS services to drive innovation and excellence.
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3+ years of experience with big data frameworks (Amazon EMR, Apache Spark) Therefore, we prioritize individuals coming from the following communities: Refugee, Neurodivergent, Single Parent, Blind or Low Vision, Deaf or Hard of Hearing, Black, Hispanic, Asian, Military Veterans, the Elderly, the LGBTQ, and Justice Impacted individuals.
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Experience working with Apache Airflow, Kafka, Spark and Hadoop. Experience working with Apache Airflow, Kafka, Spark and Hadoop. The Northrop Grumman Mission Systems (NGMS) Microelectronics Design and Applications business pushes the boundaries of innovation, redefining the leading edge of exotic new technologies in computation, system security, and AI. Among our most challenging and exciting fields are Artificial Intelligence (AI) and Transformational Computing (TC.
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Microelectronics Design and Applications (MDA) engineering is seeking a data engineer who will make significant and ongoing contributions to the maturation of our data driven processes. The Northrop Grumman Mission Systems (NGMS) Microelectronics Design and Applications business pushes the boundaries of innovation, redefining the leading edge of exotic new technologies in computation, system security, and AI.
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Experience with big data tools: Hadoop, Hive, PySpark, Apache Spark, MLlib, and GraphX. Proficient in some or all of the following techniques - Linear & Logistic Regression, Decision Trees, XG Boost, Random Forests, K-Nearest Neighbors, Markov Chain, Monte Carlo, Gibbs Sampling, Evolutionary Algorithms, Support Vector Machines.
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Experience with big data technologies such as Apache Spark or Hadoop Preferred. Experience with big data technologies such as Apache Spark or Hadoop Preferred. Experience in Machine Learning engineer or Infrastructure roles, with a focus on Machine Learning infrastructure.
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Skilled with big data processing frameworks such as Pig, MapReduce and Spark to scale algorithms over large volumes of data. Experience with Apache NiFi, Class loading, Multi-threading concurrency development, JUnit, Mokito.
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Exposure to big data technologies (e.g., Apache Spark, Hadoop, MapReduce) Here, you're an invaluable member of the team, making a real impact in a collaborative, supportive environment that truly appreciates your individual spark.
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Experience with Apache NiFi and/or Apache Spark. Experience developing applications using NoSQL (i.e. MongoDb, Elasticsearch), advanced key store (i.e. REDIS), and/or relational (i.e. Oracle, MySQL) databases.
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Strong programming skills in languages such as Python, Java, or Scala, with experience in data processing frameworks like Apache Spark or Apache Flink. Data Processing Frameworks: Implement and optimize data processing frameworks and technologies, such as Apache Hadoop, Apache Spark, and Apache Flink, to enable efficient data processing and analysis.
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Strong understanding of cloud infrastructure, services and protocols like EHRs, EMRs, Athena, Scala, Databricks, Snowflake, Spark, RDS, glue, Redshift, Apache airflow, SQS, SNS. Azure Data Factory,Azure DevOps, Azure Storage Data Lake, Extraction, Transformation and Loading.
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Knowledge of big data technologies such as Apache Spark. Experience with Databricks for data engineering and analytics preferred. Knowledge of big data technologies such as Apache Spark. Familiarity with data visualization tools (e.g., Tableau, Power BI.
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