Data Science Lead

Data Science Lead

Job Summary

As a Data Science Lead, you define the data architecture for large software projects, guide teams of data engineers through ambiguity, and set standards for engineering excellence. You lay data foundations that support long-term strategic goals.

Will be responsible for designing, implementing, and maintaining the data architecture and BI solutions that support our business operations and strategic goals. This role requires a deep understanding of data modeling, data warehousing, ETL processes, and BI tools, along with excellent problem-solving and analytical skills.

Responsibilities

• Responsible for architectural decision-making in data engineering, ensuring scalability and alignment with the company's technical vision and strategy.
• Design and develop data systems to achieve goals, while also documenting for maintainability. Knowledge of Data lakes is required
• Review and provide feedback on coworkers' changes, and lead by example by delivering first-class code.
• Investigate complex issues, design better solutions, learn from misprocessing, and implement long-term mitigations.
• Cover requirements by working with data engineer, Business Analysts, and stakeholders.
• Data Architecture Design: Develop and maintain the overall data architecture, ensuring it supports current and future BI and analytics needs, ensuring scalability and alignment with technical vision and strategy.
• Data Modeling: Create and manage logical, physical, and conceptual data models to support business requirements.
• Data Warehousing: Design, implement, and optimize data warehouses and data marts to facilitate efficient data storage and retrieval.
• ETL Processes: Develop and manage robust ETL processes to ensure data is accurately extracted, transformed, and loaded into data warehouses.
• BI Solutions: Design and implement BI solutions using tools such as Tableau, Power BI, or other relevant technologies to provide actionable insights to stakeholders.
• Data Integration: Integrate data from various sources, ensuring data quality and consistency across the organization.
• Performance Optimization: Monitor and optimize the performance of BI solutions and data architectures.
• Collaboration: Work closely with business stakeholders, data analysts, and other IT teams to understand business needs and translate them into effective data solutions.
• Documentation: Create and maintain comprehensive documentation for data architecture, data models, ETL processes, and BI solutions.
• Compliance and Security: Ensure data architectures and BI solutions comply with relevant data privacy and security regulations and best practices.

• Create frameworks with long-term ROI, establish standards for engineering excellence, identify risks and opportunities, and motivate action.
• Work under Agile methodology always updating last status, creating new tasks, and advising to the team in case of any block.
• Train and mentor less experienced engineers to set directions for other engineers.
• Define testing strategy for data projects to prevent operational incidents.
• Oversee the execution of change management activities and support CI/CD

Qualifications

• Bachelors degree in Computer Science or in a related field
• At least 7 years of experience on complex data projects, technologies for data integration and BI systems to complete collaborative software project.
• Proficiency in ETL tools (Azure Data Factory or AWS Glue or Apache Airflow etc.)
• Extensive experience in data architecture, data lakes, and data warehousing.
• Strong knowledge of big data technologies (e.g., Hadoop, Spark).
• Advanced experience in writing code in Java/Python, either on general programming ability or data processing ability with several data formats (CSV/TSV/JSON/XML).
• Advanced experience in SQL query languages and general setting databases, columnar databases, preferably Azure Synapse.
• Experience in NoSQL query/engine in general setting databases, preferably Redis or MongoDB.
• Expert knowledge of database designs for Data warehouse.
• Sound knowledge of retail and/or manufacturing management systems, CRM, and ERP solutions
• Fluency architecting and documenting architecture at multiple levels (high-level to detailed) and across multiple views (conceptual, logical, physical, data flow and sequence diagrams)

• Experience using Azure DevOps for CI/CD
• Experience in Architecture with cloud platforms like Azure or AWS is a must
• Experience with Analytics tools like Tableau, PowerBI, GoodData

Demonstrated Skills

• Able to influence, and promote change aligned with best practices
• Technical leadership skills with a strategic and analytical mindset
• Strong conflict resolution skills presenting solutions
• Organized, able to easily establish priorities, and comfortable working within a hybrid team in knowledge and locations.
• Comfortable collaborating with all levels of the business (executives, leadership, others)
• Team players but also able to work autonomously when required
• Self starter, comfortable taking initiative, motivated, and driven for success
• Experience with AI/ML and predictive analytics
• Experience with data security and compliance
• Experience and with data lifecycle management, data-tiering and data archiving

Technologies

• Microsoft Azure (Synapse Analytics)
• Tableau Administration and Content – Security Management
• Proficiency in dbt, Python, Airflow, Spark
• Relational DBMS, API, JSON and other Data sources
• Data Fabric, Snowflake, Databricks or Azure Data Lake