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Familiarity with big data and cloud technologies such as Hadoop, Spark, AWS, Azure, Google Cloud, Snowflake, and Databricks. Deep experience in data integration, data analytics, data warehousing (3NF, Star Schemas), Big Data architectures (Data Lakes, Lakehouses), and Streaming Architectures.
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As a data engineering team that supports the central finance team within Amazon, our primary customer will always be our CFO. Hence a day to day activity of a Sr. big data engineer within this team will mostly revolve around solving data engineering problems for transforming our ever growing financial data.
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Data Architecture & Tools: modern cloud data platforms (Snowflake, Databricks, Big Query, RedShift), data analytics tools (Tableau, Looker, Power BI), data programming models (DataFrames, pandas), and AI (Python, R, Jupyter Notebooks, data wrangling, machine learning.
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Proficiency with data warehouses (e.g., Snowflake, SQL Server, Redshift, Big Query, etc.) Advanced-Data Architecture : Architect and refine a scalable, robust cloud data architecture within AWS or GCP, integrating Snowflake for data warehousing, SQL Server for database management, and leveraging Python, SSIS, and DataStage for complex ETL processes.
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Familiarity with big data technologies and platforms (Dask, BigQuery, Kafka, Spark Structured Streaming). Big Data Technologies, experience in managing and analyzing large-scale datasets.
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Java | Angular | TypeScript | AWS Cloud | SQL | Big Data | Spring Boot | Databricks | Cassandra | Kubernetes | Microservices | Spark | Databricks |. It also means that our focus is on taking care of our Members and our employees, rather than having a big bottom line.
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Softrams is a Maryland and Virginia-based small business information technology, consulting, and solutions provider specializing in emerging technologies for UX/UI, mobile apps, DevOps, big data analytics, data science, and cyber security.
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Experience with big data technologies (Spark, Clickhouse, Redshift, Snowflake etc.) Proven success in communication with database users, software engineers and senior management to collect requirements, discuss data modeling decisions and define data engineering strategies.
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Big Data & Streaming: 2+ years using big data and/or streaming technologies (e.g. Apache Spark, Apache Kafka, Apache Flink) Data: Good understanding of data & data processing tools (e.g. Spark, Kafka, SQL), of relational database technologies and of analytics databases (e.g. Redshift, Vertica, Snowflake.
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The Data Standards specialist will be responsible for overseeing the development, maintenance, and documentation of a knowledge architecture that is intended to integrate reference terminology from distributors (e.g., SNOMED CT , LOINC , RxNorm) in a common data model.
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Solid background in Big Data infrastructure, Clould Infrastructure and Software Management. Experience with Big Data processing frameworks such as EMR, Athena and Big Query.
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Experience with health data standards and terminology tools (e.g., SNOMED CT, LOINC, RxNorm, UMLS, VSAC) in Health IT systems. Experience with extract, transform, load (ETL) data integration processes.
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Strong understanding of databases and big data software technologies, specifically Azure and Databricks. Strong knowledge Data structures, Data Engineering concepts, Algorithms, Collections, Multi-threading and memory management and concurrency.
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Our client is looking for Lead Python Web Developer to join their Big Data and Advanced Analytics department. We are currently seeking an experienced Python Web Developer to join the Big Data and Advanced Analytics department.
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The resource will be a SME team lead and specialist to a cross-disciplinary team of medical informaticists and data engineers to help encode and structure data in formats parse-able by java engineering teams.
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big data jobs Title: risk management Company: Dice in OK, Nebraska
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