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Master's degree in a technical field (e.g. computer science, math, engineering Understanding of big data and real time streaming analytics processing architecture and ecosystems Experience with data analysis and data visualization tools Software development experience in relevant programming languages (i.e. Java, Python, Scala, Node.js) Relevant technology or platform certification (AWS, Microsoft, etc.
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Exposure to big data tools: dbt, SnowPark, Spark, Kafka, etc. License(s)/Certification(s)/Registration(s) Required: SnowPro Advanced Data Engineer and Epic Certifications (Epic Clarity/Caboodle Data Models) required, or ability to obtain within 36 months of hire date.
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Familiarity with data engineering concepts and tools such as data pipelines, ETL processes, SQL, and big data technologies (e.g., Apache Spark, Hadoop). We are seeking a skilled Sr. Martech Software Engineer with expertise in marketing technology platforms (CRM or CDP) such as Adobe Experience Platform (AEP) or similar (e.g. Salesforce, Dynamics, etc), coupled with strong skills in building custom solutions on AWS, proficiency in API development using languages like Python or Java, and some experience in data engineering.
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Lead the evaluation and selection of data management technologies and tools, including cloud-based technologies such as Snowflake and big data processing technologies such as Apache Spark.
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Strong Experience with cloud-based data warehouses - e.g., Snowflake, Big Query, Synapse, RedShift, etc. Identify data needs for business and product teams, understand their specific requirements for metrics and analysis, and build efficient and scalable data pipelines to enable data-driven decisions across DICKs.
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Experience with big data technologies (Spark, Clickhouse, Redshift, Snowflake etc.) Define data engineering standards and best practices and drive operational excellence. 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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Experience with data warehouse solutions like Redshift, Snowflake, or BigQuery, and data orchestration tools such as Apache Airflow. Familiarity with distributed data processing frameworks such as Apache Spark or Hadoop.
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Familiarity with AI frameworks and tools such as TensorFlow, PyTorch, and OpenAI. Familiarity with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, Google Cloud, Azure.
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Create, maintain and monitor data flows in Spark, Hive, SQL and Presto for consistency, accuracy and lag time. Presto - fast parallel data warehouse and data federation layer. Create different consumers for data in Kafka using Spark Streaming for near time aggregation.
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Ability to code with scripting languages such as Python, Bash, groovy etc.,Experience with Container Orchestration platforms such as Docker, Kubernetes etc.,Experience with big data toolset: Hadoop, Spark, Kafka, Hive, sqoop etc.
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This role is critical in harnessing the power of Big Data, Lakehouse, Data Virtualization, Transformation and Integration technologies to enhance our product offerings and drive business growth.
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Your sense of ownership is needed as you take on responsibility for data compliance and data access honesty reporting for Refinitiv and direct relationship exchanges in Americas, managing Americas accrual inventory system including managing the accrual to allowable limits and reconciling and resolving accrual variance.
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Experience building data pipelines/ETL and familiarity with design principles (Apache Airflow is a big plus!) Experience with data warehouse technologies and relevant data modeling best practices (Presto, Athena, Glue, etc.
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Knowledge of, or experience with, healthcare data standards such as HL7, FHIR, ICD, SNOMED, LOINC. Comfortable working with unstructured and semi-structured data (Web scraping). As a Principal Data Engineer, you will work within the Informatics team and contribute to Tendo's strategic data engineering solutions by ingesting, transforming, and warehousing healthcare-related data from various sources.
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Big data pipeline engineering and optimization. Profound knowledge of AWS Data services (eg: Redshift, S3, EMR, Glue, RDS, Kinesis, etc.) Participate in the overall strategic direction of the data engineering technology stack.
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big data jobs Company: Local Staffing in Elkins Park, PA
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