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    Analytics Engineer - Minneapolis, United States - TechWish

    TechWish
    TechWish Minneapolis, United States

    3 weeks ago

    Default job background
    Description
    Sample 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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