Data Scientist

Key Skills

Python Programming, Scala Programming, C++, Java Programming, Machine learning techniques, Data science techniques, SQL, Apache Hadoop, MapReduce, TensorFlow, PyTorch

Job Description

The Data Science Consultant (Data Engineer) will have proven expertise in system architecture, database design, data integrations, and be an expert in SQL and Python. Experience with delivering in big data platforms such as Google BigQuery, Microsoft Azure SQL DB/Synapse, or Amazon Redshift is essential. Expertise with traditional RDBMS platforms such as SQL Server or Oracle and NoSQL and Hadoop environments would complement. Data integration experience using ETL platforms such as AirFlow, Talend, Alteryx, or Fivetran is important.

Experience in the digital data and analytic ecosystem and intermediate knowledge in Web Analytic tools (Google Analytics or the Adobe Marketing Cloud), and API expertise is a major plus!!

• Act as primary consultant to clients for data engineering services, managing the client relationship and coordinating across other support and consultant roles
• Estimate projects involving data integration, data architecture, business analysis or application development and collaborate with sales and client success teams to grow accounts
• Participate in product roadmap discussions and identifying key areas for improvement of products and services
• Collect client project requirements, focusing on needs & impacts and necessary technical outcomes
• Create solution designs to solve for clients business and technical needs while keeping within budget
• Produce documentation of data pipeline design and solution architecture for data warehousing and ETL, following Cardinal Path's documentation standards
• Create datasets, extracts, or views of data that will be consumed by teams of analysts and data scientists to support data mining, analytics, reporting, and dashboards
• Develop, implement, and support methodologies, standards, and tools for data management, considering innovation and data security
• Create ongoing standards and process for overall data architecture team, including developing governance, support and testing models
• Perform exploratory data validation with analysts to ensure quality data standards are in place and ensure data integrity during all transformation steps.

Qualifications

• Bachelor’s degree in a technical field of study (Information Systems, Computer Science, Engineering, Mathematics, Statistics, Business Analysis, etc) with a minimum of 3-5 years experience with database development 
• Experience with cloud / big data technologies such as BigQuery, Azure SQL DB/Synapse, Amazon Redshift is required
• Experience with relational database systems including SQL Server, Oracle, MySql, Postgres
• Advanced skills in data scripting and database development technologies (SQL, Python, R)
• Deep knowledge of ETL tools and how they can be applied to a big data environment
• Familiarity with analyzing digital marketing, advertising and ecommerce data
• Familiarity with web analytics tools such as Adobe Marketing Cloud or Google Analytics
• Experience with optimizing BI or visualization tools such as Tableau, Looker, DOMO or Power BI
• Experience with cloud platforms such as AWS, Azure, and Google Cloud
• Familiar with NoSql database technologies such as MongoDB
• Knowledge of technologies such as Spark, Hadoop, and Airflow