.About this role.As a Sr Principal in the Tech Market Insights Data Science team, you will be responsible for designing, developing, and maintaining the infrastructure and systems required for data storage, processing, and analysis.This is a crucial role in building and managing the data pipelines that enable efficient and reliable data integration, transformation, and delivery for data users across the team.What you will do.Design and develop data pipelines that extract data from various sources, transform it into the desired format, and load it into the appropriate data storage systems.Collaborate with data scientists and analysts to optimize models and algorithms for data quality, security, and governance.Integrate data from different sources, including databases, data warehouses, APIs, and external systems.Ensure data consistency and integrity during the integration process, performing data validation and cleaning as needed.Transform raw data into a usable format by applying data cleansing, aggregation, filtering, and enrichment techniques.Optimize data pipelines and data processing workflows for performance, scalability, and efficiency.Monitor and tune data systems, identify and resolve performance bottlenecks, and implement caching and indexing strategies to enhance query performance.Implement data quality checks and validations within data pipelines to ensure the accuracy, consistency, and completeness of data.Establish and enforce data standards, naming conventions, and data classification frameworks.Establish the governance of data and algorithms used for analysis, analytical applications, and automated decision making.What you will need.Master's degree in computer science, data science, software engineering, information systems, or related quantitative field.6+ years of professional experience in data management disciplines, including data integration, optimization and data quality, or other areas directly relevant to data responsibilities and tasks.Ability to collaborate within and across teams of different technical knowledge and work across business lines to describe business use cases/outcomes, data sources and management concepts, and analytical approaches/options.Expert problem-solving skills, including debugging skills, allowing the determination of sources of issues in unfamiliar code or systems, and the ability to recognize and solve repetitive problems.Proficiency using one or more ETL tools for data integration and workflow automation.Experience with Python, R, relational DB (SQL, NoSQL, etc.
), SPSS, APIs, and web scraping tools to gather data from various sources.Familiarity with the design and implementation of modern data architectures and concepts such as cloud services (AWS, Azure, GCP) and modern data warehouse tools (Snowflake, Databricks).Who you are.Data driven and analytical by nature with demonstrable passion for data, analytics and tools