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Utilize programming languages like Java, Scala, Python and Open Source RDBMS and NoSQL databases and Cloud based data warehousing services such as Redshift and Snowflake. 4+ years of data warehousing experience (Redshift or Snowflake.
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As a Capital One Lead Data Engineer, you'll have the opportunity to be on the forefront of driving a major transformation within Capital One. Lead Data Engineer. 4+ years experience with Distributed data/computing tools (MapReduce, Hadoop, Hive, EMR, Kafka, Spark, Gurobi, or MySQL.
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As a Senior Data Engineer on the MMA National IT Data and Analytics Team, we will count on you to develop and maintain scalable data pipelines, enhance data models, and provide subject matter expertise in data acquisition and consumption pipelines on Azure, Databricks and Confluent.
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Learn more about what makes us different and how you can thrive as a Senior Data Engineer at MMA National. Data bricks, Microsoft Azure Data Engineer, and/or other cloud certifications.
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Expertise in data storage technologies such as relational databases (e.g., PostgreSQL, MySQL), NoSQL databases (e.g., MongoDB, Cassandra), data warehouses (e.g., Snowflake, Redshift), and data lakes (e.g., Amazon S3, Azure Data Lake Storage.
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Position Overview: As the Lead Data Systems Engineer, you will play a pivotal role in leading our data systems engineering initiatives and driving the design, implementation, and optimization of our data systems infrastructure.
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If you're a seasoned engineer with expertise in data systems technologies and a proven track record of leadership in delivering successful data projects, we invite you to lead our team in this exciting opportunity.
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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: Lead the implementation and optimization of 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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Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform, and services like AWS Glue, Azure Data Factory, or Google Dataflow. 8+ years of experience in data engineering or systems engineering, with a focus on data systems technologies.
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Data Governance: Establish and enforce data governance policies and procedures to ensure data quality, security, and compliance with regulatory requirements. Performance Optimization: Lead efforts to optimize data systems performance through indexing, partitioning, and other techniques, ensuring scalability and responsiveness for analytical and reporting needs.
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Data Integration: Lead efforts to integrate data from diverse sources and systems into data systems infrastructure, ensuring data consistency, integrity, and security. Data Storage Solutions: Architect and implement data storage solutions, including relational databases, NoSQL databases, data warehouses, and data lakes, ensuring optimal performance, reliability, and scalability.
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Strong understanding of data integration concepts and techniques, with experience integrating data from diverse sources and systems in data systems infrastructure. Apply now to join our team and be part of the data revolution.
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We're committed to building cutting-edge data systems that enable efficientdata management, processing, and analysis. Proven leadership experience, with a track record of successfully leading data systems engineering teams and delivering complex projects.
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Join us and lead our efforts in shaping the future of data systems engineering. Data Systems Architecture: Lead the design and implementation of scalable and reliable data systems architecture to support the organization's data needs, including data storage, processing, and analytics.
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Documentation and Best Practices: Define and promote best practices for data systems engineering, ensuring clear and comprehensive documentation to facilitate understanding and collaboration among team members.
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