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Your expertise in ETL, Databricks, Python, Spark, Scala, JavaScript/JSON, SQL, and Jupyter Notebooks will be essential in ensuring efficient data processing and analysis. High level of proficiency in ETL processes and demonstrated, hands-on experience with technologies such as Databricks, Python, Spark, Scala, JavaScript/JSON, SQL, and Jupyter Notebooks.
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Design, develop, and implement end-to-end data pipelines, utilizing ETL processes and technologies such as Databricks, Python, Spark, Scala, JavaScript/JSON, SQL, and Jupyter Notebooks. Knowledge of Qlik/Qlik Sense, QVD/QlikView, and Qlik Production Application Standards (QPAS) is a significant plus.
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Location & Travel: The Data Engineer position will be an on-site role based at the Pentagon in Northern VA. Security Clearance: The Data Engineer must be a United States Citizen and hold a current DoD TS/SCI security clearance.
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Your expertise in Apache Spark (Scala), Apache Airflow, AWS Glue, Python, Kubernetes, and Oracle will be crucial in ensuring efficient data processing, storage, and retrieval. Design, develop, and deploy robust data pipelines and workflows using Apache Spark (Scala) and Apache Airflow to support data processing and transformation activities.
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You will have an opportunity to work on the application service layer written in Spark and Scala running on EMR’s orchestrated by Python Lambdas, debug application and environment issues, and optimize compute utilization at Capital One.
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Understanding of data modeling/visualization, database design principles, and data governance practices. Perform data cleansing, data integration, and data quality assurance activities to maintain the accuracy and integrity of large datasets.
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Knowledge of Qlik/ Qlik Sense, QVD/ QlikView, and Qlik Production Application Standards (QPAS) is a huge plus. Stay updated with emerging trends and advancements in data engineering and recommend suitable tools and technologies for continuous improvement.
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Utilize programming languages like Scala, Java, Python, SQL and GO and NoSQL databases and Cloud based data warehousing services such as Redshift and Snowflake. You will be working with Scala, Morphir IR, Go, Python, AWS (Fargate, EMR, Glue, S3), Cassandra, DynamoDB, Snowflake etc., and will have great opportunities to learn and contribute to the success of the platform.
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BigBear.ai's customers, which include the US Intelligence Community, Department of Defense, the US Federal Government, as well as customers in manufacturing, healthcare, commercial space, and other sectors, rely on BigBear.ai's solutions to see and shape their world through reliable, predictive insights and goal-oriented advice.
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Implement and enforce data governance policies and procedures, ensuring compliance with regulatory requirements and industry best practices. Secret clearance is required; TS/SCI clearance is preferred.
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Your expertise in ETL, DataBricks, Python, Spark, Scala, JavaScript/JSON, SQL, and Jupiter Notebooks will be essential in ensuring efficient data processing and analysis. Job Responsibilities:- Design, develop, and implement end-to-end data pipelines, utilizing ETL processes and technologies such as DataBricks, Python, Spark, Scala, JavaScript/JSON, SQL, and Jupyter Notebooks.
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Additionally, knowledge of Data Lakehouse technologies like Apache Iceberg or Databricks will be a significant advantage, enabling you to further enhance our data management capabilities. Utilize Python to create scalable and reusable code for data manipulation and data engineering tasks.
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Languages: Familiarity or proficiency in languages commonly used in data science, like Python, R, or Scala. Familiarity or experience with developing solutions for proposal within any of U.S. Government Agencies, to include but not limited to the following: Department of Transportation (e.g., FAA), NASA (including JPL), Department of Commerce (e.g., NOAA), or Department of Energy (e.g., HQ, NNSA.
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Deep Learning: Understanding neural networks, backpropagation, architectures like CNNs, RNNs, transformers, and tools like TensorFlow, PyTorch, or Keras. Distributed Computing: Tools like Apache Spark, Hadoop.
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Minimum of 5 years of hands-on skills in Python, Apache Spark, Hive, Cassandra, Snowflake, Elastic, Lucene, DataBricks, Hadoop, Redshift, Scala, Java, or other relevant technologies in data engineering.
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scala job in Alexandria, VA
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