About the role
We are looking for a Data Engineer who has hands-on experience designing and building data lakes and scalable data pipelines. The ideal candidate will have experience working with modern cloud-based data infrastructure and building reliable pipelines that power analytics, reporting, and machine learning use cases. You will work closely with data scientists, analysts, and product teams to design robust data systems and ensure high-quality, accessible data across the organization.
Responsibilities:
- Design, build, and maintain scalable data pipelines to ingest, transform, and process large volumes of data.
- Build and manage data lakes and modern data platforms on cloud environments.
- Develop ETL/ELT workflows to integrate data from multiple internal and external sources.
- Ensure data reliability, quality, and governance across the data ecosystem.
- Optimize data pipelines for performance, scalability, and cost efficiency.
- Collaborate with data scientists, analysts, and engineering teams to support analytics and machine learning workflows.
- Implement data modeling and schema design to support business intelligence and reporting.
- Monitor and troubleshoot data pipelines and infrastructure issues.
Requirements:
- 3-6 years of experience in data engineering or similar roles.
- Strong experience building data pipelines and ETL/ELT workflows.
- Hands-on experience with data lake architecture and modern data platforms.
- Strong programming skills in Python or Scala.
- Experience working with SQL and large datasets.
- Experience with cloud platforms such as AWS, GCP, or Azure.
- Familiarity with data orchestration tools (Airflow, Prefect, etc. ).
- Experience with data warehousing solutions such as Snowflake, BigQuery, or Redshift.
- Strong understanding of data modeling, data transformation, and pipeline optimization.
Preferred Qualifications:
- Experience working with streaming data pipelines.
- Exposure to analytics or ML data workflows.
- Experience with containerization and cloud infrastructure.
- Understanding of data governance and data quality frameworks.