Associate Staff Engineer -- Data Analyst

Company Description

We are a Digital Product Engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work at scale — across all devices and digital mediums, and our people exist everywhere in the world (19,500+ experts across 35+ countries, to be exact). Our work culture is dynamic and non-hierarchical. We are looking for great new colleagues. That is where you come in!

Job Description

Must have skills : Power BI (Capable), Python (Capable), SQL (Strong), SQL Server, Snowflake

Job Description: 

• General Experience and Skills
  • 4+ years’ experience in the data & analytics space
  • Good communication skills
  • Ability to articulate findings and challenges found in analysis and during SQL Development
  • Ability to listen attentively to capture notes and feedback during requirements sessions.
  • Requirements Gathering & Business Acumen
  • Experience collecting requirements from business stakeholders and translating into technical data requirements.
  • Ability to relate and understand how data supports business objectives and strategy.
  • Experience with building data analyst consumer facing data structures (tables, views, small data marts)
  • Strong data analysis skills
  • Experience with exploratory data analysis with new datasets.
  • Foundational descriptive statistics experience (e.g., mean, median, mode, standard deviation, skewness)
  • Experience with unit testing developed tables and views.
  • Experience with identifying and resolving data quality issues.

• Technical Skills
  • Strong general SQL experience & fluency
  • CTEs, Window Functions, Joins, Group By, Where, Having, Stored Procedures / UDFs
  • DDL/DML to create/alter/insert/delete tables and views
  • AWS Cloud Data Analyst Experience
  • Athena, S3, Glue, EMR Studio (for Jupyter Notebooks)
  • Foundational Data Modeling Knowledge & Concepts
  • Star & Snowflake schema structures
  • Slowly changing dimensions
  • Normalization & Denormalization
  • Data Warehouse / Data Lake / Data Lakehouse concepts
  • Basic Python Experience
  • Pandas, Numpy, SQLAlchemy, Requests (for API Requests)
  • Basic Spark Experience & Concepts
  • Comfort with SparkSQL and using Spark data frames
  • Foundational experience with creating and updating YAML-based configuration files
  • Experience working in Jupyter Notebooks with SQL, Python, SparkSQL
  • Foundational API Experience
  • Understanding of pagination and cursor concepts for retrieving multiple responses
  • Experience using a tool like Postman, Curl statements, and/or the Python requests libraries to write requests (GET/POST) to retrieve and interpret sample payloads from APIs
  • Basic Power BI Experience
  • Connecting to basic data sources (SQL Server, Snowflake, and )
  • Developing basic dashboard visualizations
  • Connecting different data sources in the Power BI data model interface.