- Design and implement scalable, secure, and efficient data pipelines and architectures on AWS
- Build ETL/ELT processes to ingest, transform, and store structured and unstructured data from diverse sources.
- Define and manage the architecture for real-time and batch data processing
- Partner with
data scientists, analysts, and business teams to understand data needs and deliver high-quality solutions.
- Stay updated with emerging AWS technologies and data engineering best practices
- Drive continuous improvement in processes, tools, and methodologies
- Troubleshoot and resolve data-related issues, ensuring data quality and accuracy
- Mentor junior data engineers, providing guidance on data/coding standards, best practices
- Bachelor's or Master's degree in Computer Science, Information Systems, Engineering, or a related field.
- 4+ years of experience as a Senior/Lead Data Engineer or in a similar role, focusing on AWS cloud solutions.
- Proven experience designing and building data architectures and pipelines.
- Expertise in AWS services, including but not limited to S3, EMR, Lambda, and RDS.
- Proficiency in SQL, Python, and Java for data processing and manipulation.
- Experience with data tool stacks such as: Spark, Flink, Airflow, Debezium, Kafka, Trino, Presto.
- Strong knowledge of data modeling, data warehousing, and data lakes.
- Strong problem-solving and analytical skills.
- Knowledge of machine learning workflows and integration with data pipelines.
- Knowledge of data lake platforms like Dremio, Snowflake, Data Brick, ...
- Strong leadership, communication, and interpersonal skills.
- Experience in mentoring and coaching junior engineers.
- Ability to develop and implement long-term data strategies.