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Lead data collection, management, and storage projects using tools like Snowflake, Amazon Redshift, Google BigQuery, Azure Synapse Analytics, Fivetran, and Talend. What You’ll Do: Serve as a strategic thought partner to C-suite executives on data initiatives, understanding client personas (CFO, CIO, CHRO, CAO) and advising on harnessing data to support strategic goals.
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Data Management & Automation: Knowledge with data systems like Snowflake or Microsoft Azure and proficient in querying and managing data using SQL or tools like Alteryx and Power Automate / Query.
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We are in search of a highly motivated candidate to join our talented Team. Job Title: Sr. Data Engineer Location(s): Mclean, VA Must have: 5+ years of experience with Python, SQL, Airflow, Spark, AWS (EMR, Lambda) Nice to have: Scala, Snowflake The candidate will be collaborating with other engineers and following the Agile Methodology.
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Using tools such as Palantir Foundry, they will also work with cutting-edge DevOps technologies, develop advanced analytics products, and apply data pipelining and statistical programming tools to enterprise data to advance and enable key mission outcomes.
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Extensive expertise with Apache NiFi Java Java Spring Boot microservices AWS (Redshift Athena) and big data technologies. Provide technical expertise in Java programming Spring Boot microservices and big data technologies in an AWS cloud environment (Redshift Athena etc.
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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. 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.
Full-timeExpandApply NowActive JobUpdated 10 days ago - UpvoteDownvoteShare Job
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Apply a variety of spatial data science techniques to tackle customer challenges to include geospatial statistics, spatial optimization, spatial pattern analysis, geospatial artificial intelligence, spatial autocorrelation, activity-based intelligence, imagery analysis, remote sensing, and geospatial data visualization approaches.
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Experience managing vulnerabilities in both on-premises systems and in cloud environments (e.g., Amazon Web Services, Microsoft Azure, Google Cloud, and Data Centers). Experience analyzing data and identifying vulnerabilities, extending beyond running a scan to analyzing systems, network configurations, web applications, and architectural diagrams, as well as identifying top vulnerabilities such as those listed in the OWASP "Top Ten" and understanding how those vulnerabilities work at the programmatic level.
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Develop and maintain insider threat risk scoring and other data analytics tools for customers to support insider threat detection and data analysis implementations. Educate relevant stakeholders in the theoretical and empirical bases of data science and behavioral science related to the deterrence, detection and mitigation of potential threats by providing or contributing to expert training briefs, presentations and educational courses.
$168,700 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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Proficient in Databricks, Python, Pyspark, Scala for developing and maintaining data engineering pipelines, with expertise in Apache Spark, Flink, and containerization. Expertise architecting, designing and building data pipelines and acquiring data needed to build and evaluate models, using tools like Databricks, Dataflow, Apache Beam, or Spark.
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Uses statistical tools such as mathematics, statistics, performance measurement, and will assist the PA team or PDCS Data Manager to advance analytics using data visualization tools such as MS Power Bl, Tableau, MS Excel, Mural, and others to generate reports and develop compelling stories that convey statistical or technical information to non-technical.
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The Research Scientist 1 designs and implements data and specimen collection methodology tools and processes to respond to research questions/inquiries. Bioinformatical data processing, FASTQ/SAV/JSON raw data parsing, and developing of data processing pipelines (preferred.
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The Geospatial Analyst job title also covers such subtitles as Data Collector, Source Packager, and Product Delivery Specialist. The geospatial analyst is a flexible role that relies on understanding of basic geospatial concepts of projection, elevation, attribution, and works in conjunction with source materials to update and/or creating new geospatial feature data sets, maps and charts, submitting work through the QA/QC process along a wide variety of mission areas and geographic settings, while meeting deadlines in a high-tempo environment.
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Data Engineering & Cloud Services: Utilize a comprehensive tech stack, including Python, Java, SQL Databases, Databricks, Docker, Azure, and AWS, to develop scalable data engineering solutions and manage cloud data analytics tools.
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Member, Eligibility (LOB, Plan), Provider, Claim data, about Risk Calculation, Care Plan Implementation, Grievance and Appeals, Patient Management Utilization Management (Authorization), Drug-Drug Interaction, Medications and Lab data Management, CDPS (Analytics) etc., Azure, EDI.
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data job Title: hadoop in Vienna, VA
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