Senior Data Engineer
Posted 22 days ago · 102 applicants
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The role in plain words
This role involves building and maintaining scalable data pipelines and platforms from the ground up, supporting both batch and real-time use cases. You will design data architectures, integrate structured and unstructured sources, and manage data lakes and warehouses. Day-to-day tasks include writing Python and SQL, working with AWS services, and orchestrating workflows using Airflow.
- 5+ years of hands-on experience as a Data Engineer, building data systems from scratch in dynamic environments
- Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent practical experience)
- Strong proficiency in Python and advanced SQL, with solid experience in data modeling
- Proven experience designing and building scalable data pipelines (batch and real-time), including streaming technologies such as Kafka
- Strong experience working with AWS, including services such as S3, Athena and DynamoDB
- Experience with data platform technologies such as Databricks, Snowflake
- Experience building data platforms using modern lakehouse technologies (e.g., Iceberg)
Extracted from the job description · kept up to date automatically
Who this suits
This role suits an experienced data engineer with over five years of hands-on experience, strong Python and SQL skills, and familiarity with AWS, Kafka, and Spark. It is less ideal for those seeking a highly structured environment, as it requires navigating ambiguous, fast-paced situations and building systems from scratch.
Full job description
Original listing · kept for referenceWe are looking for a strong, hands-on Data Engineer to join our team and play a key role in building our data infrastructure from the ground up. In this role, you will design and implement scalable data pipelines and platforms, supporting both batch and real-time use cases. You will work closely with analysts and stakeholders to deliver reliable, high-quality data solutions, and take full ownership of data flows - from ingestion to consumption. This is a great opportunity for an executor who enjoys building, moving fast, and making an impact. What will your job look like?
• Design, build, and maintain robust and scalable data pipelines (batch and real-time) end-to-end.
• Design and implement scalable, flexible data architectures to support evolving business needs.
• Build and manage data platforms, including data lakes and data warehouses.
• Integrate multiple data sources (structured and unstructured) into a unified data platform using batch (ETL) and real-time streaming solutions.
• Design and implement efficient data models, schemas, and database structures (SQL / NoSQL).
• Develop and implement data quality processes to ensure accuracy, consistency, and reliability.
• Monitor, optimize, and troubleshoot data infrastructure to meet performance and SLA requirements.
All you need is:
• 5+ years of hands-on experience as a Data Engineer, building data systems from scratch in dynamic environments.
• Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent practical experience).
• Strong proficiency in Python and advanced SQL, with solid experience in data modeling.
• Proven experience designing and building scalable data pipelines (batch and real-time), including streaming technologies such as Kafka.
• Strong experience working with AWS, including services such as S3, Athena and DynamoDB.
• Experience working with big data processing frameworks such as Spark, and columnar data formats (e.g., Parquet).
• Hands-on experience with workflow orchestration tools such as Airflow.
• Strong ownership and execution mindset, with excellent problem-solving skills and high attention to detail, and the ability to collaborate effectively and deliver in ambiguous, fast-paced environments.
• Experience with data platform technologies such as Databricks, Snowflake - Advantage.
• Experience building data platforms using modern lakehouse technologies (e.g., Iceberg) - Advantage.
• Fluent in English.
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Questions about this role
- This listing did not state a salary. We only show pay when the employer publishes it.
- 5+ years of hands-on experience as a Data Engineer, building data systems from scratch in dynamic environments, Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent practical experience), Strong proficiency in Python and advanced SQL, with solid experience in data modeling, Proven experience designing and building scalable data pipelines (batch and real-time), including streaming technologies such as Kafka, Strong experience working with AWS, including services such as S3, Athena and DynamoDB