Responsibilities:
- Lead, mentor, and expand a diverse team of professionals, including 7 data engineers, data scientists, and data analysts, fostering an environment of growth and innovation.
- Spearhead the development and implementation of scalable data pipelines and architectures, ensuring impeccable data quality and accessibility for advanced analytics and machine learning applications.
- Oversee all aspects of extraction, transformation, and loading (ETL) processes.
- Actively collaborate with business stakeholders to identify and gather essential data, driving data science initiatives that support and enhance product development, analytics, and machine learning projects aligned with our company's strategic objectives.
- Manage the data warehouse and data lake infrastructure, ensuring robust data modeling, efficient ETL processes, and the incorporation of big data technologies. Stay abreast of the latest advancements in Python, SQL, Snowflake, and Google Cloud Platform (GCP) to maintain a cutting-edge data environment.
- Champion the adoption of industry-leading practices in data governance, security, and compliance to protect sensitive information and adhere to regulatory standards.
- Drive continuous improvement in our data engineering and data science processes by staying informed of emerging technologies and trends, recommending strategic technological advancements.
- Ensure the creation and regular update of technical documentation, and oversee rigorous unit testing and troubleshooting to maintain system integrity and performance.
Qualifications:
- Minimum 5 years of experience in roles related to Data Engineering, Data Architecture, Data Management, Business Analysis, Business Intelligence, MIS, System Management, or similar fields.
- At least 2 years of experience in leadership positions, with a proven track record of managing and mentoring teams, especially in the realm of data science.
- Fluent in English, with excellent written and spoken communication skills, capable of engaging effectively with business partners.
- Advanced proficiency in Microsoft Excel and a solid understanding of containerization concepts (e.g., Docker).
- Strong foundational knowledge of database concepts, data modeling, SQL, and a demonstrated ability in Python and SQL (DML, DDL, DQL).
- Experience with Microsoft SQL Server, Google BigQuery, Snowflake, Apache Airflow, and SSIS is highly desirable.
- Familiarity with BI tools such as Tableau and Looker Studio, showcasing a capacity to derive insights and support data-driven decision-making.
- A committed team player with outstanding communication skills, a keen passion for continuous learning, and a drive to stay at the forefront of technological advancements in a dynamic environment.