Python
PostgreSQL
Amazon Web Services (AWS)DATA ENGINEER
Overview
They started with a singular belief - what is beautiful cannot and should not be defined in marketing meetings. It's defined by the regular people like us, our sisters, our next-door neighbours, and the friends we make on the playground and in lecture halls. That's why we stand for people-proving everything we do. From the inception of a product idea to testing the final formulations before launch, our consumers are a part of each and every process. They guide and inspire us by sharing their stories with us. They tell us not only about the product they need and the skincare issues they face but also the tales of their struggles, dreams and triumphs. Skincare goes deeper than skin. It's a form of self-care for many. Wherever someone is on this journey, we want to cheer them on through the products we make, the content we create and the conversations we have. What we wish to build is more than a brand. We want to build a community that grows and glows together - cheering each other on, sharing knowledge, and ensuring people always have access to skincare that really works.
Job Description:
We are seeking a skilled and motivated Data Engineer to join our team. As a Data Engineer, you will be responsible for designing, developing, and maintaining the data infrastructure and systems that enable efficient data collection, storage, processing, and analysis. You will collaborate with cross-functional teams, including data scientists, analysts, and software engineers, to implement data pipelines and ensure the availability, reliability, and scalability of our data platform.
Responsibilities:
Design and implement scalable and robust data pipelines to collect, process, and store data from various sources.
Develop and maintain data warehouse and ETL (Extract, Transform, Load) processes for data integration and transformation.
Optimize and tune the performance of data systems to ensure efficient data processing and analysis.
Collaborate with data scientists and analysts to understand data requirements and implement solutions for data modeling and analysis.
Identify and resolve data quality issues, ensuring data accuracy, consistency, and completeness.
Implement and maintain data governance and security measures to protect sensitive data.
Monitor and troubleshoot data infrastructure, perform root cause analysis, and implement necessary fixes.
Stay up-to-date with emerging technologies and industry trends in data engineering and recommend their adoption when appropriate.
Qualifications:
Bachelor’s or higher degree in Computer Science, Information Systems, or a related field.
Proven experience as a Data Engineer or similar role, working with large-scale data processing and storage systems.
Strong programming skills in languages such as Python, Java, or Scala.
Experience with big data technologies and frameworks like Hadoop, Spark, or Kafka.
Proficiency in SQL and database management systems (e.g., MySQL, PostgreSQL, or Oracle).
Familiarity with cloud platforms like AWS, Azure, or GCP, and their data services (e.g., S3, Redshift, BigQuery).
Solid understanding of data modeling, data warehousing, and ETL principles.
Knowledge of data integration techniques and tools (e.g., Apache Nifi, Talend, or Informatica).
Strong problem-solving and analytical skills, with the ability to handle complex data challenges.
Excellent communication and collaboration skills to work effectively in a team environment.
Preferred Qualifications:
Advanced knowledge of distributed computing and parallel processing.
Experience with real-time data processing and streaming technologies (e.g., Apache Kafka, Apache Flink).
Familiarity with machine learning concepts and frameworks (e.g., TensorFlow, PyTorch).
Knowledge of containerization and orchestration technologies (e.g., Docker, Kubernetes).
Experience with data visualization and reporting tools (e.g., Tableau, Power BI).
Certification in relevant technologies or data engineering disciplines.
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