Dice
W2 - Analytics Engineer (Data engineering, Data Modeling, ETL, Data analysis, SQ
Dice, Saint Paul, Minnesota, United States, 55199
Dice
is the leading career destination for tech experts at every stage of their careers. Our client, Tanson Corp, is seeking the following. Apply via Dice today!
Description:
Analytics EngineerInterviews
will be held via Microsoft Teams.Project Schedule
Anticipated Project Start Date: June, 2024Anticipated End Date: June, 2026Sample Tasks
Create datasets for analytical purposes, including datasets for end users to import into desktop tools, and datasets for BI developers to import into analytics and BI tools.Build semantic layers and models that enable the rest of the organization to consume analytics more efficiently.Build the data pipelines that feed into data science and machine learning models.Deliver well-defined, transformed, tested, documented, and code-reviewed datasets for analysis.Build data aggregation pipelines using Python, Apache Airflow, Spark, SQL, etc.Create robust data models and architectures to support analytics initiatives.Identify and implement optimizations to continually enhance query performance, reduce processing time, and increase overall productivity.Design, develop and maintain data pipelines to ensure efficient and reliable ETL processes.Implement and maintain analytics systems, data warehouses, or data lakes to store and manage structured and unstructured data.Create and maintain dashboards, visualizations, and reports using tools such as Tableau, Power BI, or Looker to enable data-driven decision-making.Ensure data quality and accuracy by implementing data validation, monitoring, and error-handling processes.Provide knowledge transfer.Qualifications
2-5 years of experience in data analytics, data engineering, software engineering, or a similar role.Expertise in data modeling, ETL development, and data analysis.Strong ability in SQL for data extraction and manipulation, and proficiency in data warehousing concepts/tools such as Redshift and Snowflake.Familiarity with cloud-based data platforms such as AWS, Google Cloud Platform, and Azure for data storage and processing.Substantial programming ability using languages/tools such as R, Python, JavaScript, Scala, and C++ for data manipulation and scripting.Solid understanding of relevant data governance, data quality, and data security best practices.Knowledge of ETL processes, data integration, and data warehousing concepts.Familiarity with data visualization tools such as Tableau, Power BI, and Looker.Knowledge of big data technologies and distributed computing frameworks such as Hadoop and Spark.Strong problem-solving skills, and the ability to think critically and analytically.Excellent communication skills to effectively collaborate with cross-functional teams and present insights to business stakeholders.Ability to collaborate with business stakeholders to understand their analytics needs and deliver comprehensive reports, dashboards, and models.W2 - Analytics Engineer (Data engineering, Data Modeling, ETL, Data analysis, SQL, Cloud) - Onsite
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is the leading career destination for tech experts at every stage of their careers. Our client, Tanson Corp, is seeking the following. Apply via Dice today!
Description:
Analytics EngineerInterviews
will be held via Microsoft Teams.Project Schedule
Anticipated Project Start Date: June, 2024Anticipated End Date: June, 2026Sample Tasks
Create datasets for analytical purposes, including datasets for end users to import into desktop tools, and datasets for BI developers to import into analytics and BI tools.Build semantic layers and models that enable the rest of the organization to consume analytics more efficiently.Build the data pipelines that feed into data science and machine learning models.Deliver well-defined, transformed, tested, documented, and code-reviewed datasets for analysis.Build data aggregation pipelines using Python, Apache Airflow, Spark, SQL, etc.Create robust data models and architectures to support analytics initiatives.Identify and implement optimizations to continually enhance query performance, reduce processing time, and increase overall productivity.Design, develop and maintain data pipelines to ensure efficient and reliable ETL processes.Implement and maintain analytics systems, data warehouses, or data lakes to store and manage structured and unstructured data.Create and maintain dashboards, visualizations, and reports using tools such as Tableau, Power BI, or Looker to enable data-driven decision-making.Ensure data quality and accuracy by implementing data validation, monitoring, and error-handling processes.Provide knowledge transfer.Qualifications
2-5 years of experience in data analytics, data engineering, software engineering, or a similar role.Expertise in data modeling, ETL development, and data analysis.Strong ability in SQL for data extraction and manipulation, and proficiency in data warehousing concepts/tools such as Redshift and Snowflake.Familiarity with cloud-based data platforms such as AWS, Google Cloud Platform, and Azure for data storage and processing.Substantial programming ability using languages/tools such as R, Python, JavaScript, Scala, and C++ for data manipulation and scripting.Solid understanding of relevant data governance, data quality, and data security best practices.Knowledge of ETL processes, data integration, and data warehousing concepts.Familiarity with data visualization tools such as Tableau, Power BI, and Looker.Knowledge of big data technologies and distributed computing frameworks such as Hadoop and Spark.Strong problem-solving skills, and the ability to think critically and analytically.Excellent communication skills to effectively collaborate with cross-functional teams and present insights to business stakeholders.Ability to collaborate with business stakeholders to understand their analytics needs and deliver comprehensive reports, dashboards, and models.W2 - Analytics Engineer (Data engineering, Data Modeling, ETL, Data analysis, SQL, Cloud) - Onsite
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