Data Engineer

What will you do?

•Design, develop and own robust data pipelines, ensuring optimal performance, scalability, and maintainability.

•Design and implement Data Lake, Dare Warehouse and Lakehouse solutions with different architecture patterns.

•Ensure data quality, integrity and governance across all stages of data lifecycle.

•Monitor and optimize performance of data engineering pipelines.

•Contribute to design principles, best practices, and documentation.

•Collaborate closely with cross-functional teams to deeply understand business requirements, translating them into effective technical design, implementations that support the organization's data-driven initiatives.

•Provide mentorship and guidance to other team members of the data engineering team, promoting knowledge transfer, a culture of continuous learning and skills development.

We are looking for:

•Bachelor's degree in computer science, Information Systems, or a related field. Master's degree is a plus.

•A seasoned Data Engineer with a minimum of 8+ years of experience.

•Deep experience in designing and building robust, scalable data pipelines – both batch and real-time using modern data engineering tools and frameworks.

•Proficiency in AWS Data Services (S3, Glue, Athena, EMR, Kinesis etc.).

•Strong grip on SQL queries, various file formats like Apache Parquet, Delta Lake, Apache Iceberg or Hudi and CDC patterns.

•Experience in stream processing frameworks like Apache Flink or Kafka Streams or any other distributed data processing frameworks like pySpark.

•Expertise in workflow orchestration using Apache Airflow.

•Strong analytical and problem-solving skills, with the ability to work independently in a fast-paced environment.

•In-depth knowledge of database systems (both relational and NoSQL) and experience with data warehousing concepts.

•Hands-on experience with data integration tools and a strong familiarity with cloud-based data warehousing and processing is highly desirable.

•Excellent communication and interpersonal skills, facilitating effective collaboration with both technical and non-technical stakeholders.

•A strong desire to stay current with emerging technologies and industry best practices in data landscape.