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Experience with modern data platforms (Azure Synapse, Databricks, Redshift, Big Query, Snowflake). Utilize programming languages like Java, Pyspark, Python and Open Source RDBMS and NoSQL databases, and Cloud-based data warehousing services such as Redshift and Snowflake.
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Experience with master data (MDM), metadata, and data governance tools. Expertise in ETL/ELT, SQL, and cloud data integration tools (Azure Data Factory, AWS Glue, Informatica.
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Skill Advancement: Work with the leadership team to develop a personalized training plan to enhance your data engineering skills. Metadata and Data Policy Management: Support and administer the implementation of metadata management and master data policies.
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In this dynamic role as a Data Engineer, you'll be at the forefront of shaping our data landscape. At least 2 years of experience in data engineering. Comprehensive foundation in SQL, data modeling, data warehousing, and data analysis.
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Here, you'll immerse yourself in a world of data management and governance, learning to design models and use advanced tools. Data Solution Implementation: Contribute to the design and execution of prototypes, proofs of concept, and data solutions.
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Expert Microsoft t-SQL and DAX development skillsExtensive experience using various data modeling techniques (Kimball, Inmon, or Data Vault)Experience using the Power Platform, particularly Power Bi and Power AutomateExperience in a multicloud environment, with a focus on GCP.
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You won't just be filling a position; you'll be embarking on a journey where your skills in designing data workflows and developing innovative data solutions will be crucial. Demonstrated ability to deliver scalable data solutions using compatible programming languages.
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You'll code with machine learning languages like DataBricks and Python Libraries to synthesize millions of data sets into patterns that answer ad hoc requests and then use Tableau for data visualization.
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Experience working with the following: AWS, GCP, Python, SQL, Terraform, Pyspark (Big Data) and Airflow. Master's Degree in Computer Science, Data Science, Engineering, Math, Science, Information Technology, Computer Applications, Management Information Systems, Computer Information Systems, Accounting, Commerce, Business Administration or related.
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Technical Integration: Develop and implement technical requirements into our data workflows, collaborating closely with your manager and senior engineers. Ability to oversee data lifecycle management, from ideation to retirement.
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As you collaborate with experienced mentors and senior engineers, your contributions will be pivotal in building enterprise-class data pipelines. Proficiency in Python, PySpark Scala, Java, SQL, Airflow, dbt.
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Familiarity with Continuous Integration and Continuous Delivery systems and tools (Azure DevOps, GitHub). Our business is guided by our people helping people philosophy which includes our team members.
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Knowledge of cloud technologies (Azure, AWS, GCP). Collaborative Development: Engage in system analysis, coding, testing, and debugging, in partnership with mentors and senior engineers. We offer the flexibility of remote work for residents in these locations, allowing you to contribute from the comfort of your own home.
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One year of experience in higher education accreditation with the following: institutional research and accreditation; teacher education program accreditation; data elements and their utilization; analyzing data; and making summary tables using Stata and Microsoft Power BI. Demonstrated ability with Excel and Google spreadsheets, and R programming language.
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O Provide visualizations and analysis of data sets in the context of assigned data-centric projects (using one or more of the following languages: R, Python, SQL, DataBricks, Spotfire, and Power BI.
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data job
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