W2 - Analytics Engineer (Data engineering, Data Modeling, ETL, Data analysis, SQL, Cloud) - Onsite

4 weeks ago


Saint Paul, United States Tanson Corp Full time
Job DescriptionJob DescriptionDescription:Analytics Engineer Interviews will be held via Microsoft Teams.Project ScheduleAnticipated Project Start Date: June, 2024
Anticipated 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.
Delivers well-defined, transformed, tested, documented, and code-reviewed datasets for analysis
Builds data aggregation pipelines using Python, Apache Airflow, Spark, SQL, etc.
Creates robust data models and architectures to support analytics initiatives
Identifies and implements optimizations to continually enhance query performance, reduce processing time, and increase overall productivity
Designs, develops and maintains data pipelines to ensure efficient and reliable ETL processes
Implements and maintains analytics systems, data warehouses, or data lakes to store and manage structured and unstructured data
Creates and maintains dashboards, visualizations, and reports using tools such as Tableau, Power BI, or Looker to enable data-driven decision-making
Ensures 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, GCP, 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

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