What youll be investing your time on:
Data Platform Strategy: Select and design data architectures, including data lakes, data warehouses (DWH) and data products, ensuring scalability, efficiency, and alignment with long-term business goals and IT strategies
Cross-functional Leadership: Bring together relevant stakeholders (product, business, R&D) to align solutions and ensure successful execution. Lead discussions between technical and business teams to ensure a comprehensive approach.
Define data management standards, including data governance, security, privacy, and compliance with relevant regulations
Data Modeling & Governance: Lead the design of data models (relational, NoSQL, data lakes, data warehouses) that support business analytics, ensuring high standards of data quality, governance, and compliance.
Implement best practices for ETL/ELT pipelines, data integration, and data quality management.
Stay up-to-date with emerging trends in data architecture, analytics, and cloud technologies, recommending improvements as needed and driving R&D efforts to explore new data technologies and methodologies that enhance the companys ability to innovate.
Mentor and provide technical guidance to data professionals.
For this role you are:
A creative thinker with an innovation mindset, always looking to develop new approaches and solutions to data challenges.
Capable of assessing the limitations and capabilities of both existing and new systems.
Skilled in troubleshooting technical issues and resolving problems efficiently.
Able to evaluate and choose the right technology to meet data needs.
Knowledgeable in software architecture principles and seeing the big picture.
A strong team player who contributes ideas, shares knowledge, and supports colleagues.
Flexible and adaptable, thriving in dynamic and fast-paced environments.
An effective communicator with strong interpersonal skills.
Have you done this kind of stuff?
10+ years of experience in data architecture, database design, and data modeling.
Strong expertise in SQL, NoSQL, and cloud-based data technologies (Google BigQuery, Snowflake, Databricks, AWS Redshift).
Proficiency in ETL/ELT tools (DBT, Dataform, Apache Spark etc.).
Knowledge and understanding of streaming & stream processing technologies such as Kafka, RabbitMQ, PubSub, Apache Flink, Spark, Dataflow
Understanding of data warehousing concepts and technologies, including data lakes, data marts, and data warehouses
Familiarity with BI tools such as Looker, Tableau, PowerBI.
Familiarity with data governance frameworks and regulatory requirements.
Strong problem-solving skills and ability to work in a fast-paced environment.
Excellent communication and stakeholder management skills.
