What You'll Do

As a member of the Data & Analytics team you will be reporting to the Digital Collaboration Portfolio. You will support data analytics; machine learning and innovation needs. The role will require working across multiple squads and engaging different stakeholders to provide insights for data driven decision making on wide ranging use cases.

The ideal candidate will ensure that our Data & Analytics team aligns to the business objectives and supports key initiatives for the squads and tribe. Role will need to leverage the latest technology and best practices to deliver results, agility, efficiency and quality for data and visualization requirements.

What You'll Bring

1. Minimum 4-8 years of relevant professional experience in Analytics roles and Data Engineering.
2. Strong proficiency in Python, focusing extensively on data engineering tasks such as data ingestion, transformation, and pipeline orchestration.
3. Hands-on experience with AWS Glue/Lambda for developing and managing ETL workflows and data pipelines.
4. Experience integrating APIs using Python for data extraction from various structured and unstructured data sources.
5. Solid experience with Snowflake, SQL, and relational database management systems, ensuring efficient data warehousing and querying.
6. Demonstrated ability in designing insightful and interactive visualizations and dashboards using Power BI or Tableau. Skilled in Power BI features such as DAX, Power Query, data modelling and integration with external APIs. Familiarity with advanced Tableau capabilities including Level of Detail (LOD) expressions, logical and physical joins, data blending, and APIs.
7. Good-to-have proficiency in developing and fine-tuning predictive models for enhancing user experiences and operational efficiency, utilizing machine learning methods such as time-series forecasting, classification techniques, decision trees, and random forests.
8. Good-to-have familiarity with Natural Language Processing (NLP), including tasks like sentiment analysis, text mining, and experience with AWS Comprehend and popular NLP libraries such as spaCy and scattertext.
9. Good-to-have practical knowledge and experience with Python visualization libraries (Plotly, Matplotlib, Seaborn) to support exploratory data analysis and effective visual communication of insights.
10. Excellent analytical, problem-solving, and communication skills to effectively collaborate with cross-functional teams.