AddressAbout The Media Ant :
The Media Ant is a 11 year-old company in the AdTech space. We aim to disrupt the traditional process of executing ad campaigns through a physical media agency and replace it with a self-serve advertising platform. The platform should work equally well for both online and offline media.
This platform will empower any advertiser, irrespective of their budget and level of marketing understanding, to be able to go ahead and launch a campaign.
The Media Ant is the winner of various startup awards and is used by more than a million users every year. Please visit our website (www.TheMediaAnt.com) to learn more.
Position Overview:
We are seeking a highly skilled and motivated Data Engineer to join our team. As a Data Engineer, you will play a key role in designing, implementing, and maintaining the data infrastructure of our organization. Your primary responsibility will be to develop and optimize data pipelines, databases, and ETL processes, ensuring the efficient and reliable flow of data across various systems. You will collaborate closely with stakeholders, analysts, and software engineers to support data-driven decision-making and enable the successful delivery of data projects.
Key Responsibilities:
- Design and develop robust, scalable, and efficient data pipelines and ETL processes to extract, transform, and load data from various sources into data warehouses or data lakes.
- Collaborate with cross-functional teams to understand data requirements and implement solutions that meet business needs.
- Build and maintain data infrastructure, including data warehouses and data processing frameworks.
- Ensure data quality and integrity by implementing appropriate data validation, monitoring, and error-handling mechanisms.
- Develop and maintain data models and schemas to support data analytics and reporting needs.
- Identify and address data-related issues and bottlenecks, ensuring the smooth operation of data pipelines and systems.
- Stay up to date with emerging technologies, tools, and best practices in Data Engineering, and actively contribute to the improvement of Data Engineering processes and workflows.
- Collaborate with the product and tech team to enable effective data exploration, analysis, and modeling.
Preferred Qualifications:
- Bachelor's or master's degree in computer science, Data Engineering, or a related field.
- 2-3 years of experience working as a Data Engineer, preferably in a fast-paced and data-intensive environment.
- Strong proficiency in Python with experience in data manipulation and scripting (Py spark).
- Solid understanding of data warehousing concepts, SQL, and experience with relational databases (e.g., PostgreSQL, MySQL) and NoSQL databases (e.g MongoDB).
- Hands-on experience with data integration and ETL tools such as Apache Airflow, Apache NiFi, Talend or Informatica.
- Must have experience with Google Big Query
- Proven experience with Web Scraping, data automation, data modeling, and data warehousing techniques.
- Strong problem-solving and analytical skills, with the ability to troubleshoot and resolve data-related issues.
- Excellent communication skills and the ability to work collaboratively in a team environment.
Good to have:
- Familiarity with data streaming technologies and real-time data processing.
- Understanding of DevOps practices and experience with containerization technologies (e.g., Docker, Kubernetes).
