Data Associate Director

We are looking for a Data Associate Director to be part of this amazing fast-growing Fintech.

The professional must assist and lead a data-focused team to support a newborn business unit while aligning the practice with the existing core products. Key responsibilities include developing data strategies, implementing governance frameworks, analyzing data for insights, and building robust data architectures. The role involves creating a collaborative team culture, managing risk and compliance, and driving continuous improvement and innovation. 

The candidate will contribute to strategic decision-making and sustainable growth in the dynamic Fintech landscape.

Key Responsibilities

1. Data Strategy Development: understand the Financial Services Business Unit goals and their relation to the company objectives to provide vision and actionable direction to data-team under your command.

2. Data Governance: Implement and enforce data governance policies and procedures to ensure data quality, integrity, privacy, and security. This includes defining data standards, metadata management, and compliance with regulatory requirements in alignment with other Data Directors in the organization.

3. Data Analysis and Insights: Oversee the analysis of large datasets to derive actionable insights and identify trends that can inform business decisions. This may involve using statistical methods, machine learning techniques, and data visualization tools.

4. Data Architecture and Infrastructure: Collaborate with IT teams to design, implement, and maintain data architecture and infrastructure that support the company's data needs. This includes selecting appropriate database technologies, data warehouses, and cloud services.

5. Data Engineering: Lead data engineering efforts to collect, process, and store data from various sources in a scalable and efficient manner. This involves designing ETL (Extract, Transform, Load) processes, data pipelines, and data integration solutions.

6. Team Leadership and Mentorship: Provide leadership and guidance to a team of data analysts, engineers, and scientists. Mentor junior team members, foster a culture of collaboration and continuous learning, and ensure that team goals align with organizational objectives.

7. Stakeholder Management: Collaborate with cross-functional teams including product management, marketing, finance, and compliance to understand their data needs and deliver solutions that meet their requirements. Act as a liaison between technical and non-technical stakeholders.

8. Risk Management: Assess and mitigate risks related to data management, including data breaches, data loss, and regulatory non-compliance. Implement security measures and disaster recovery plans to safeguard sensitive information.

Technical knowledge

 Data Management:

• Understanding of database systems (relational databases like MySQL, PostgreSQL, and NoSQL databases like MongoDB, Cassandra).

• Knowledge of data modeling techniques to design efficient and scalable databases.

• Familiarity with data warehousing concepts and platforms such as Amazon Redshift, Google BigQuery, or Snowflake.

• Experience with data integration tools and techniques for extracting, transforming, and loading (ETL) data from various sources.

2- Data Analytics and Visualization:

• Ability to develop and interpret complex SQL queries for data analysis.

• Proficiency in statistical analysis and data mining techniques.

• Experience with analytical tools and languages such as Python (with libraries like Pandas, NumPy, SciPy), R, or MATLAB.

• Familiarity with data visualization tools such as Tableau, Power BI, or matplotlib/seaborn in Python.

3- Machine Learning and Predictive Analytics:

• Understanding of machine learning algorithms and techniques for predictive modeling, classification, clustering, and regression.

4- Big Data Technologies:

• Experience with distributed computing frameworks such as Apache Spark.

• Knowledge of cloud-based big data platforms like AWS or GCP.

• Understanding of containerization technologies like Docker and orchestration tools like Kubernetes for deploying and managing big data applications.

5- Data Security and Compliance:

• Awareness of data security principles and best practices to ensure the confidentiality, integrity, and availability of data.

• Experience implementing security controls, encryption techniques, and access management policies.

6- Programming and Scripting:

• Proficiency in programming languages such as Python or Java for developing data pipelines, applications, and automation scripts.

7- Software Development Lifecycle:

• Understanding of software development methodologies such as Agile or DevOps, and their application to data projects.

At Clip we embrace and honor the differences of our Clippers, and together we create a vibrant and extraordinary culture in a space where everyone can be their true self and thrive to their full potential.
We promote access to the same opportunities in a safe and respectful space, free of discrimination and harassment.
Diversity, equity and inclusion have been part of Clip since its foundation and are a key part of our essence. Together we make the extraordinary happen!
If you are unstoppable, creative and have the skills we need, we want to hear from you!

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