Analytics Engineer

1 month ago


Minneapolis, United States TechWish Full time
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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